system

Abstract

We provide the system. [Solution] A means of collecting environmental data in real time from environmental monitoring equipment, A means for analyzing the aforementioned collected environmental data within a cloud environment, A means for predicting environmental changes and disaster risks based on the analyzed data, A means for detecting an anomaly and generating an alarm based on the aforementioned prediction, A means of providing specific countermeasures along with the aforementioned warning, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, 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 times when environmental problems are intensifying, there is a demand for real-time collection and analysis of detailed environmental data, and further rapid prediction of risks associated with environmental changes. However, in conventional systems, these processes are fragmentary, and there are problems that it is difficult to detect abnormalities at an early stage and present specific countermeasures. In addition, the effective utilization of information such as visualization of collected data and generation of reports is insufficient, which hinders rapid decision-making. 【Means for Solving the Problems】 【0005】 This invention utilizes a sensor network and an autonomous unmanned aerial vehicle as an observation device for collecting environmental data in real time. The collected data is analyzed in a cloud environment, and AI is used to predict environmental changes and disaster risks. Based on the prediction results, anomalies are detected, warnings are immediately generated, and specific countermeasures are provided. Furthermore, the analyzed data is visualized as geographic information, and an interface is provided to make the information easy for users to understand visually, thereby providing a means to streamline the entire process from environmental monitoring to countermeasures. 【0006】 An "environmental monitoring device" is a device that uses sensor networks and autonomous unmanned aerial vehicles to collect environmental data in real time. 【0007】 A "sensor network" is a system in which numerous geographically dispersed sensors are interconnected to collect and transmit environmental data. 【0008】 An "autonomous unmanned aerial vehicle" is an aircraft that flies autonomously according to a program without direct operation by a pilot, and collects environmental data. 【0009】 A "cloud environment" is a computing environment that utilizes computing resources and storage provided via the internet to perform data analysis and storage. 【0010】 "AI" is artificial intelligence technology that processes large amounts of data and performs analysis and prediction by mimicking human intelligence. 【0011】 "Anomaly detection" is the process of identifying deviations from normal conditions and pinpointing potential hazards or problems. 【0012】 An "alarm" is a notification or signal that alerts us to the occurrence of an abnormality, and its role is to encourage a quick response. 【0013】 "Countermeasures" refer to actions or measures taken in response to a specific problem, meaning means to prevent the problem from worsening and lead to its resolution. 【0014】 "Geographic information" is a concept that refers to information that includes data about location and space, and is related to a specific geographical area. 【0015】 An "interface" is the part that serves as a window for users to interact with a system, and is a means of inputting and outputting information. [Brief explanation of the drawing] 【0016】 [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 the data processing device and 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]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine. 【Mode for Carrying Out the Invention】 【0017】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0018】 First, the terms used in the following description will be explained. 【0019】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0020】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0021】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0022】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0023】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0024】 [First Embodiment] 【0025】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0026】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0027】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0028】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0029】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0030】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0031】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0032】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0033】 As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0034】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0035】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0036】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0037】 This invention provides a system for collecting environmental data in real time by using a sensor network and an autonomous unmanned aerial vehicle as environmental observation devices. This system performs analysis in a cloud environment and enables AI-based prediction of environmental changes and disaster risks. Furthermore, it is designed to immediately issue an alarm and provide specific countermeasures if an anomaly is detected. 【0038】 Specifically, the server manages a sensor network and autonomous unmanned aerial vehicles for data collection. These devices measure temperature, humidity, pollutant concentrations, and other environmental data in specific areas. The collected data is transmitted to the server via wireless communication and stored in a cloud environment. 【0039】 The server utilizes high-performance analysis algorithms in the cloud to analyze the received environmental data. AI technology is used for data analysis, and by comparing it with historical data, it is possible to predict future environmental changes and disaster risks. For example, based on historical data, it is possible to predict the impact of air pollution in a specific area on health and to understand environmental changes in advance. 【0040】 If an anomaly is detected, an alert is sent to the device in real time. This allows users to quickly obtain information and take appropriate countermeasures. For example, if air pollution is worsening in a particular area, users will be advised to stay indoors or wear a filter mask. 【0041】 Furthermore, the terminal uses a geographic information system to visualize the collected data on a map. This visualization is important because it shows the environmental conditions of each region, making it easier for users to intuitively understand changes in the environment. 【0042】 Furthermore, this system automatically generates environmental reports periodically based on the analysis results. This allows users to comprehensively understand changes over time and utilize this information for long-term environmental conservation activities. For example, it can be used to monitor long-term temperature changes in a particular region and provide data for taking measures against climate change. 【0043】 By combining these features, this invention enables the efficient collection and analysis of environmental data, as well as prediction and response based on that data, thereby contributing to the realization of a sustainable global environment. 【0044】 The following describes the processing flow. 【0045】 Step 1: 【0046】 The server sends data collection commands to the sensor network and autonomous unmanned aerial vehicles. This activates each device, which then begins collecting environmental data in a pre-configured area. 【0047】 Step 2: 【0048】 The terminal receives real-time data transmitted from sensors and unmanned aerial vehicles. This includes information such as temperature, humidity, and pollutant concentrations. 【0049】 Step 3: 【0050】 The server sends the received data to a cloud environment where it is stored and initially analyzed. Data cleaning and normalization are performed to prepare the data for analysis. 【0051】 Step 4: 【0052】 The server uses AI algorithms to perform in-depth analysis on stored data. By comparing it with past data, it identifies patterns in environmental changes and predicts future fluctuations and anomalies. 【0053】 Step 5: 【0054】 Based on predictions made by the AI ​​model, the server detects anomalies. If an anomaly is identified, it quickly generates an alert and develops countermeasures according to the predicted risk level. 【0055】 Step 6: 【0056】 The terminal receives alarms and countermeasure information sent from the server. This allows the user to obtain this information in real time and take necessary actions immediately. 【0057】 Step 7: 【0058】 Users will take action based on the countermeasures provided. For example, they will follow instructions such as wearing a mask or closing windows in response to predicted air pollution. 【0059】 Step 8: 【0060】 The terminal visualizes the data analyzed by the system as geographical information. This allows users to intuitively understand the current environmental conditions and predicted changes on a map. 【0061】 Step 9: 【0062】 The server automatically generates and distributes weekly and monthly environmental reports to users on a regular basis. These reports include comparisons with historical data and trend analysis, which is helpful for considering long-term countermeasures. 【0063】 (Example 1) 【0064】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0065】 There is a need to rapidly and accurately predict risks from environmental changes and natural disasters, and to provide appropriate countermeasures. However, conventional environmental monitoring systems suffer from delays in data collection and analysis, resulting in insufficient real-time prediction and warning issuance. Furthermore, visualization for intuitive understanding of collected data and the presentation of concrete countermeasures are inadequate. Therefore, an efficient system that integrates environmental information collection, analysis, prediction, warning, and countermeasure provision is required. 【0066】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0067】 In this invention, the server includes means for collecting environmental information in real time from an environmental monitoring device, means for analyzing the collected environmental information within an information processing environment, and means for predicting environmental changes and natural disaster risks by comparing them with past data using a high-performance analysis algorithm. This enables efficient collection of environmental information and the provision of highly accurate future predictions, rapid warnings, and countermeasures. 【0068】 "Environmental monitoring equipment" refers to a system that includes sensors and devices for measuring and recording environmental information. 【0069】 "Real-time" refers to processing and analysis of information as close as possible to the moment it is collected. 【0070】 "Environmental information" refers to data related to the natural environment, such as temperature, humidity, and pollutant concentrations. 【0071】 An "information processing environment" refers to a computer system or cloud platform where data analysis, storage, and computational processing are performed. 【0072】 A "high-performance analysis algorithm" refers to a computational method used to process data efficiently and accurately and perform complex analyses. 【0073】 "Anomaly detection" refers to the process of identifying data or predictions that deviate from normal patterns. 【0074】 An "alarm" refers to a notification or warning issued when an abnormality is detected. 【0075】 "Response measures" refer to the actions or measures to be taken in response to detected anomalies. 【0076】 A "report" refers to a document that summarizes analysis results, warnings, and countermeasures. 【0077】 A "user interface" refers to a screen or device that allows humans to operate and view the functions and information of a system. 【0078】 This invention describes an embodiment of a system that collects and analyzes environmental information in real time, detects anomalies, and provides appropriate countermeasures. First, a server controls environmental monitoring equipment and collects environmental information for a specific area using a group of sensors and unmanned aerial vehicles. This includes measuring temperature, humidity, and pollutant concentrations. The collected environmental information is transmitted to the server using wireless communication technology and stored in cloud storage. 【0079】 The server uses high-performance analytical algorithms and AI technology to analyze stored data. The AI ​​model predicts future environmental changes and natural disaster risks based on historical data. If an abnormal data pattern is detected, the server generates an alarm and sends it to the terminal in real time. 【0080】 When the device receives this alert, it uses a geographic information system to visualize environmental information, and the user makes a judgment based on this information. Specific countermeasures recommended on the device include refraining from going outside and wearing a filter mask. 【0081】 Furthermore, the server periodically integrates the analysis results and automatically generates environmental reports. These reports include historical data and forecast information, and are available to users in PDF and HTML formats. 【0082】 For example, if the concentration of carbon dioxide in the atmosphere rises sharply in a certain area, the server analyzes the data using an AI model and assesses the health risks. Based on this assessment, an alert is quickly sent to the terminal, and specific countermeasures are suggested to the user. 【0083】 An example of a prompt message for a generating AI model might be: "Based on carbon dioxide concentration data from the past 24 hours, predict future health risks and suggest countermeasures." 【0084】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0085】 Step 1: 【0086】 The server activates the sensor device and collects environmental information for a specified area. The input is raw data measured by the sensor (temperature, humidity, pollutant concentration, etc.). This data is transmitted to the server using wireless communication. The output is raw environmental data, which is stored in cloud storage. Specifically, the sensor periodically monitors the surrounding environment and transmits the data in real time. 【0087】 Step 2: 【0088】 The server processes raw data stored in the cloud using high-performance analytical algorithms. The input is unprocessed data stored in cloud storage. Data processing involves cleaning and analyzing the data using statistical methods and AI models. The output is analytical results based on comparisons with historical data. Specifically, the AI ​​model detects anomalous patterns and predicts future environmental changes and natural disaster risks. 【0089】 Step 3: 【0090】 The server generates an alarm if an anomaly is detected based on the analysis results. The input consists of data obtained in the analysis step and prediction results. The server processes this data to determine if an anomaly is present and creates an alarm if necessary. The output is an alarm message, which is sent to the terminal. Specifically, the alert is communicated to the user via email or app notifications. 【0091】 Step 4: 【0092】 The terminal visualizes received alarms using a Geographic Information System (GIS). Inputs include alarm messages and analysis results sent from the server. The GIS system processes this data to create an intuitive map display. The output provides the user with a map showing the environmental conditions. Specifically, the user interface displays regional alarm levels and countermeasures in an easy-to-understand format. 【0093】 Step 5: 【0094】 The user takes appropriate action based on the information presented. Inputs include warning information and a map display from the device. Based on this, the user decides on specific actions. The output is the user's action plan. Specific actions include taking situation-appropriate measures such as staying indoors or wearing a filter mask. 【0095】 (Application Example 1) 【0096】 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." 【0097】 In modern society, environmental changes in urban areas directly impact the lives and health of citizens. However, conventional environmental monitoring devices have limited data collection capabilities, making it difficult to provide real-time predictions and warnings. This creates a challenge in taking swift and appropriate measures in response to environmental changes. 【0098】 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. 【0099】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information within a cloud infrastructure, and means for visualizing the analyzed data as geographic information and displaying it on a mobile device. This enables citizens to check the environmental conditions around them at any time and take prompt action to prevent health damage. 【0100】 "Environmental monitoring equipment" refers to devices that collect environmental information such as temperature, humidity, and pollutant concentrations in a specific area. 【0101】 "Real-time" refers to processing and transmission of information at a time close to the moment it is generated. 【0102】 A "cloud infrastructure" is a distributed computing environment that provides data storage and computing processing over the internet. 【0103】 "Analysis" refers to methods and processes for revealing trends and characteristics in collected data. 【0104】 "Geographic information" refers to location data about specific points or regions, as well as related supplementary information. 【0105】 A "mobile device" is a portable communication device such as a mobile phone or tablet. 【0106】 "Citizen" refers to an ordinary individual residing in a particular region or city. 【0107】 "Health damage" refers to the potential for changes in the environment or living conditions to negatively affect a person's health. 【0108】 This invention is a system for smart cities that collects, analyzes, and visualizes environmental data in real time. The system consists of a server, terminals, and users. 【0109】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. This aggregates the environmental information, ensuring that the latest data is always stored within the cloud infrastructure. To process the collected data, the server executes high-performance analysis algorithms on the cloud infrastructure. For specific analyses, AI frameworks such as TENSORFLOW® are used. 【0110】 The terminal is a mobile device such as a smartphone or tablet, and it presents information to the user through a mobile application based on analyzed data received from the server. Using geographic information systems such as Leaflet.js, the collected data can be displayed on an intuitive map. This allows users to visually understand the environmental conditions of their surrounding area. 【0111】 This system allows users to receive real-time alerts about environmental changes. These alerts include risks such as worsening air pollution and rising temperatures, and based on this, specific countermeasures (e.g., staying indoors, using a mask with a filter) are suggested. 【0112】 In generating a specific program, the following prompt can be used: "Based on the city's air pollution data for the past week, assess this week's forecast and potential health hazards, and suggest necessary preventative measures." This prompt allows the generated AI model to analyze the data and suggest countermeasures. 【0113】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0114】 Step 1: 【0115】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. The input is data from environmental sensors, and the output is transmitted to the cloud infrastructure. This data collection is automated, allowing for real-time, up-to-date information to be constantly maintained. 【0116】 Step 2: 【0117】 The server analyzes data collected using TensorFlow on a cloud infrastructure. The input is environmental data collected in step 1, and the output is analysis results that detect anomalies. The analysis uses a generative AI model to compare past and present data and predict future environmental changes and disaster risks. 【0118】 Step 3: 【0119】 The server generates an alarm based on the analysis results and formulates specific countermeasures. The input is the analysis results from step 2, and the output is the generated alarm and countermeasures. Specifically, if the system detects the progression of abnormal air pollution, it issues specific instructions to citizens to refrain from going outside. 【0120】 Step 4: 【0121】 The terminal displays the analysis results and alarms received from the server on the mobile device. The input is the alarms and countermeasures generated in step 3, and the output is the information displayed on the user interface. Leaflet.js is used to display visualized map information on the terminal, making it easy for the user to understand intuitively. 【0122】 Step 5: 【0123】 The user selects an appropriate action based on the information provided through the device. The input is the warnings and countermeasures displayed in step 4, and the output is the user's specific action (e.g., refrain from going outside). Based on the surrounding environmental information, the user can make appropriate decisions to prevent health damage. 【0124】 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. 【0125】 This invention provides a system that combines environmental data collected by an environmental monitoring device with an emotion engine that recognizes user emotions, and provides warnings and countermeasures tailored to the user's emotions. The aim of this system is to improve the user experience and provide more personalized countermeasures. 【0126】 Specifically, the server collects environmental data using a sensor network and autonomous unmanned aerial vehicles. The collected data is analyzed in a cloud environment to predict environmental changes and disaster risks. Based on these analysis results, the server detects anomalies and generates alarms. 【0127】 Simultaneously, the emotion engine operates, and the device collects the user's voice data, facial expression data, and biometric data. The emotion engine analyzes this data to determine the user's emotional state. For example, it analyzes various emotional states, such as whether the user is stressed or relaxed. 【0128】 The server considers the analyzed emotional data and adjusts the alerts and responses in a way that is optimal for the user. For example, if the user is feeling stressed, the system will deliver the alert in a calm tone and suggest relaxing techniques as a response. 【0129】 This personalized information is delivered to the user through their device. The device uses a geographic information system to visualize the results of environmental analysis on a map, presenting the information in a way that the user can intuitively understand. In addition, messages are displayed that are tailored to the user's emotional state, and emotionally sensitive encouragement or warnings are added. 【0130】 Through this series of processes, the system can simultaneously perform environmental monitoring and provide psychological support to users, enabling better countermeasures and increased peace of mind. This achieves both environmental protection and improved user confidence. 【0131】 The following describes the processing flow. 【0132】 Step 1: 【0133】 The server issues commands to the sensor network and autonomous unmanned aerial vehicles to collect environmental data. The devices activate and collect data such as temperature, humidity, and air quality in the specified area. 【0134】 Step 2: 【0135】 The terminal receives real-time environmental data transmitted from sensors and unmanned aerial vehicles. This data is transferred wirelessly to a database in the cloud. 【0136】 Step 3: 【0137】 The server analyzes incoming data in a cloud environment. Large-scale data processing algorithms are used for analysis, including purification and normalization. Based on the analysis results, potential environmental changes and disaster risks are predicted using AI algorithms. 【0138】 Step 4: 【0139】 If the server detects an anomaly based on the collected environmental data, it immediately generates an alarm and prepares to warn the user. 【0140】 Step 5: 【0141】 The device captures the user's voice data, facial expressions, and biometric information and transmits it to the emotion engine. 【0142】 Step 6: 【0143】 The server uses an emotion engine to analyze the user's emotional data. An emotion analysis model is used to determine the user's emotional state, such as stress or relaxation. 【0144】 Step 7: 【0145】 The server adjusts alarm messages and responses based on the user's emotional state. It determines the message tone and content according to the user's stress level and psychological state, and creates alarm notifications. 【0146】 Step 8: 【0147】 The device displays tailored warning messages to the user and visualizes environmental conditions as geographical information. It also presents the user with recommended actions that include emotionally sensitive encouragement and warnings. 【0148】 Step 9: 【0149】 Users take action based on the information presented. By taking actions that take into account environmental conditions and their personal psychological state, they can effectively mitigate risks and alleviate psychological burden. 【0150】 (Example 2) 【0151】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0152】 This invention aims to solve the problem of providing more personalized information and psychological support by offering warnings and response measures that take into account the user's emotional state, in addition to predicting environmental changes and disaster risks. Conventional systems analyze environmental data, but they are insufficient in providing response measures that take into account the user's emotional state, resulting in problems where they are limited to mere warning notifications. 【0153】 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. 【0154】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information in a remote information processing environment, and means for collecting the user's voice, facial expressions, and biosignals and performing emotion analysis. This makes it possible to provide adaptive and personalized warnings and countermeasures according to the user's emotional state. 【0155】 "Environmental monitoring equipment" refers to devices and sensors used to collect environmental information, and which have the function of acquiring physical or chemical data in real time. 【0156】 A "remote information processing environment" is an environment that utilizes cloud-based computing resources used to collect, analyze, and store data. 【0157】 "Emotion analysis" is the process of evaluating and identifying a user's psychological state and emotions based on their voice, facial expressions, and biosignals. 【0158】 A "personalized alert" is warning information that is customized based on the individual user's emotional state and circumstances, and delivered in an appropriate format. 【0159】 "Adaptive and personalized responses" refer to methods that integrate and analyze environmental information and the user's emotional state to provide users with optimized behavioral guidelines and recommendations. 【0160】 The system in this invention mainly consists of environmental monitoring equipment, a server, and a terminal. The role of each element and how the invention is implemented are shown below. 【0161】 The server collects environmental information acquired in real time from environmental monitoring equipment. This equipment includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. This data is sent to a cloud computing platform (e.g., a typical cloud service provider), where machine learning algorithms are used for data analysis. This analysis predicts environmental changes and the risk of disasters. 【0162】 Simultaneously, the device collects the user's voice, facial expressions, and biosignals to perform emotion analysis. The device uses smartphones and wearable devices to acquire the user's voice data and biometric data such as heart rate. This data is analyzed in a remote information processing environment to determine the user's emotional state. 【0163】 Once the analysis results are obtained, the server integrates and analyzes the collected environmental information and user emotion data. Based on these results, personalized alerts and responses are generated and appropriately adjusted. For example, a user experiencing tension might receive an alert message in a calm tone along with recommendations for relaxation. 【0164】 Users receive visualizations of environmental information via geographic information systems provided through their devices, as well as messages that take their emotional state into consideration. For example, if an abnormal weather event occurs nearby, a message such as "Please move to a safe place immediately. We will support you so that you can act with peace of mind" will be displayed. This entire process provides users with a sense of security and offers better countermeasures against emerging environmental risks. 【0165】 An example of a prompt to input into the generation AI model would be: "Generate weather information notifications that take into account the user's emotional state. If the user is feeling anxious, add a calming message." This allows the system to deliver appropriate information based on the situation. 【0166】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0167】 Step 1: 【0168】 The server collects environmental information in real time from environmental monitoring equipment. This process includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. The environmental data, as input, is sent to the server and stored on a cloud computing platform. Specifically, the sensors periodically acquire data and upload it to the server using wireless communication technology. 【0169】 Step 2: 【0170】 The server analyzes the collected environmental data within a remote information processing environment. The environmental data, as input, is analyzed using machine learning algorithms, and the output predicts environmental fluctuations and disaster risks. Specifically, the data analysis leverages cloud-based processing power to detect anomalous data patterns and generate warnings for future risks. 【0171】 Step 3: 【0172】 The device collects the user's voice, facial expressions, and biosignals. This collection process primarily utilizes smartphones and wearable devices. Voice data and biosignal data, as input, are acquired by the device and transmitted to a server. Specifically, the device captures voice with a microphone, facial expressions with a camera, and measures heart rate with a biosensor. 【0173】 Step 4: 【0174】 The server analyzes voice, facial expression, and biosignal data sent from the user. This includes a process that uses a generative AI model to determine the user's emotional state. The input is voice and biosignal data, and the output is the user's emotional state (e.g., stress, exhilaration, relaxation). Specifically, individual emotional state tags are generated based on the analysis results. 【0175】 Step 5: 【0176】 The server integrates environmental information and user sentiment data to generate alarms and countermeasures. Inputs include predicted environmental change data and user sentiment data. From this, the server outputs personalized alarm messages and countermeasures. Specifically, if an abnormality alarm is required, the alarm message is constructed in a tone appropriate to the user's emotional state. 【0177】 Step 6: 【0178】 The terminal presents the user with generated alarms and countermeasures. Input consists of alarm data and countermeasures from the server. The terminal outputs and displays this information in a user-friendly format. Specifically, it visualizes the alarm message on the terminal screen and provides audio warnings as needed. Using a geographic information system, information related to the user's location is also displayed on a map. 【0179】 Through these steps, the system can monitor environmental changes in real time and provide users with the most appropriate and emotionally sensitive information. 【0180】 (Application Example 2) 【0181】 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 device 14 will be referred to as the "terminal." 【0182】 Conventional environmental monitoring systems have struggled to provide warnings and countermeasures that take into account the user's psychological state, limiting their ability to improve the user experience and provide personalized countermeasures. Furthermore, the visualization of environmental data can sometimes be difficult to understand intuitively, and further improvements are needed. Therefore, the present invention aims to realize the provision of environmental information that responds to the user's emotions, thereby improving their sense of security and convenience. 【0183】 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. 【0184】 In this invention, the server includes means for immediately accumulating data from a device that acquires environmental information, means for analyzing the accumulated data in an information processing environment, and means for identifying the user's emotional state and providing personalized countermeasures along with warnings. This makes it possible to provide optimal environmental information and countermeasures according to the user's psychological state. 【0185】 A "device for acquiring environmental information" refers to a device used to instantly collect data on the surrounding environment. 【0186】 "Information processing environment" refers to a system that includes computing infrastructure and cloud services for analyzing accumulated data. 【0187】 "Emotional state" is an indicator that shows the user's psychological and physiological condition, and is information analyzed from voice and facial expression data. 【0188】 "Personalized solutions" refer to customized solutions and suggestions tailored to the user's emotional state. 【0189】 An "information display device" is a device that provides information to users visually, and includes smartphones and displays. 【0190】 A "sensor group" is a system composed of multiple sensors, and is a group of devices used to acquire various environmental data. 【0191】 An "autonomous aircraft" is an aircraft that has the ability to collect data while flying autonomously without a driver. 【0192】 "Biometric information" refers to data that indicates the user's physical condition, and includes things like heart rate and body temperature. 【0193】 To implement this invention, first, a device for acquiring environmental information is deployed. Environmental data such as temperature, humidity, noise, and air quality are collected using a group of sensors or an autonomous aircraft. The data from these devices is immediately transmitted to an information processing environment located in the cloud. 【0194】 The server processes the collected environmental data using advanced data analysis techniques. This analysis utilizes Google Cloud and TensorFlow, applying models to predict environmental changes and disaster risks. Based on the predicted results, if an anomaly is detected, an appropriate warning is generated and notified to the user. 【0195】 Meanwhile, the user's smartphone sends biometric information such as voice, heart rate, and facial expressions to an emotion analysis engine. This analysis uses an AI model based on TensorFlow to determine the user's emotional state in real time. For example, if the system determines that the user is feeling stressed, relaxation strategies are automatically selected. 【0196】 The user's device displays analysis results along with suggested actions and advice tailored to their emotional state. The information is visualized on a map and presented in an easy-to-understand format. For example, if the system determines the user is experiencing high stress, a message such as, "There's a relaxing park nearby. Why not stop by?" might be displayed. 【0197】 This system can provide users with optimal information and advice by inputting prompts into a generative AI model. An example of a prompt for the generative AI model would be, "Please tell me about nearby relaxation spots that I can use right now. The user is experiencing high stress." In this way, a system integrating environmental observation and emotion recognition can be realized, contributing to an improved user experience. 【0198】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0199】 Step 1: 【0200】 The server instantly receives environmental data such as temperature, humidity, noise, and air quality from devices that acquire environmental information. The input sensor data is sent to the cloud and aggregated on Google Cloud. This enables real-time environmental monitoring. 【0201】 Step 2: 【0202】 The server applies a data analysis model using TensorFlow to analyze the collected environmental data. Using the environmental data as input, it predicts environmental fluctuations and disaster risks, and generates a warning if an anomaly is detected. The output of this process is whether or not an anomaly was detected and the warning message. 【0203】 Step 3: 【0204】 The user's device sends biometric information such as voice, heart rate, and facial expression data to the emotion analysis engine. A TensorFlow AI model uses this data as input to analyze the user's emotional state. The output is the user's emotional state, such as "relaxed" or "highly stressed." 【0205】 Step 4: 【0206】 The server generates warnings and personalized responses based on analyzed emotional states and environmental data. It uses emotional states and environmental anomaly information as input, and prompts a generating AI model to determine the optimal advice. The output is a message displayed to the user. 【0207】 Step 5: 【0208】 The user's device uses the outputted message to utilize a geographic information system to visualize environmental information and countermeasures on a map. This makes it easy for users to intuitively check the information and implement countermeasures. Users can easily check detailed information and countermeasures by tapping on markers on the map. 【0209】 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. 【0210】 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. 【0211】 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. 【0212】 [Second Embodiment] 【0213】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0214】 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. 【0215】 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). 【0216】 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. 【0217】 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. 【0218】 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). 【0219】 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. 【0220】 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. 【0221】 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. 【0222】 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. 【0223】 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. 【0224】 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". 【0225】 This invention provides a system for collecting environmental data in real time by using a sensor network and an autonomous unmanned aerial vehicle as environmental observation devices. This system performs analysis in a cloud environment and enables AI-based prediction of environmental changes and disaster risks. Furthermore, it is designed to immediately issue an alarm and provide specific countermeasures if an anomaly is detected. 【0226】 Specifically, the server manages a sensor network and autonomous unmanned aerial vehicles for data collection. These devices measure temperature, humidity, pollutant concentrations, and other environmental data in specific areas. The collected data is transmitted to the server via wireless communication and stored in a cloud environment. 【0227】 The server utilizes high-performance analysis algorithms in the cloud to analyze the received environmental data. AI technology is used for data analysis, and by comparing it with historical data, it is possible to predict future environmental changes and disaster risks. For example, based on historical data, it is possible to predict the impact of air pollution in a specific area on health and to understand environmental changes in advance. 【0228】 If an anomaly is detected, an alert is sent to the device in real time. This allows users to quickly obtain information and take appropriate countermeasures. For example, if air pollution is worsening in a particular area, users will be advised to stay indoors or wear a filter mask. 【0229】 Furthermore, the terminal uses a geographic information system to visualize the collected data on a map. This visualization is important because it shows the environmental conditions of each region, making it easier for users to intuitively understand changes in the environment. 【0230】 Furthermore, this system automatically generates environmental reports periodically based on the analysis results. This allows users to comprehensively understand changes over time and utilize this information for long-term environmental conservation activities. For example, it can be used to monitor long-term temperature changes in a particular region and provide data for taking measures against climate change. 【0231】 By combining these features, this invention enables the efficient collection and analysis of environmental data, as well as prediction and response based on that data, thereby contributing to the realization of a sustainable global environment. 【0232】 The following describes the processing flow. 【0233】 Step 1: 【0234】 The server sends data collection commands to the sensor network and autonomous unmanned aerial vehicles. This activates each device, which then begins collecting environmental data in a pre-configured area. 【0235】 Step 2: 【0236】 The terminal receives real-time data transmitted from sensors and unmanned aerial vehicles. This includes information such as temperature, humidity, and pollutant concentrations. 【0237】 Step 3: 【0238】 The server sends the received data to a cloud environment where it is stored and initially analyzed. Data cleaning and normalization are performed to prepare the data for analysis. 【0239】 Step 4: 【0240】 The server uses AI algorithms to perform in-depth analysis on stored data. By comparing it with past data, it identifies patterns in environmental changes and predicts future fluctuations and anomalies. 【0241】 Step 5: 【0242】 Based on predictions made by the AI ​​model, the server detects anomalies. If an anomaly is identified, it quickly generates an alert and develops countermeasures according to the predicted risk level. 【0243】 Step 6: 【0244】 The terminal receives alarms and countermeasure information sent from the server. This allows the user to obtain this information in real time and take necessary actions immediately. 【0245】 Step 7: 【0246】 Users will take action based on the countermeasures provided. For example, they will follow instructions such as wearing a mask or closing windows in response to predicted air pollution. 【0247】 Step 8: 【0248】 The terminal visualizes the data analyzed by the system as geographical information. This allows users to intuitively understand the current environmental conditions and predicted changes on a map. 【0249】 Step 9: 【0250】 The server automatically generates and distributes weekly and monthly environmental reports to users on a regular basis. These reports include comparisons with historical data and trend analysis, which is helpful for considering long-term countermeasures. 【0251】 (Example 1) 【0252】 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". 【0253】 There is a need to rapidly and accurately predict risks from environmental changes and natural disasters, and to provide appropriate countermeasures. However, conventional environmental monitoring systems suffer from delays in data collection and analysis, resulting in insufficient real-time prediction and warning issuance. Furthermore, visualization for intuitive understanding of collected data and the presentation of concrete countermeasures are inadequate. Therefore, an efficient system that integrates environmental information collection, analysis, prediction, warning, and countermeasure provision is required. 【0254】 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. 【0255】 In this invention, the server includes means for collecting environmental information in real time from an environmental monitoring device, means for analyzing the collected environmental information within an information processing environment, and means for predicting environmental changes and natural disaster risks by comparing them with past data using a high-performance analysis algorithm. This enables efficient collection of environmental information and the provision of highly accurate future predictions, rapid warnings, and countermeasures. 【0256】 "Environmental monitoring equipment" refers to a system that includes sensors and devices for measuring and recording environmental information. 【0257】 "Real-time" refers to processing and analysis of information as close as possible to the moment it is collected. 【0258】 "Environmental information" refers to data related to the natural environment, such as temperature, humidity, and pollutant concentrations. 【0259】 An "information processing environment" refers to a computer system or cloud platform where data analysis, storage, and computational processing are performed. 【0260】 A "high-performance analysis algorithm" refers to a computational method used to process data efficiently and accurately and perform complex analyses. 【0261】 "Anomaly detection" refers to the process of identifying data or predictions that deviate from normal patterns. 【0262】 An "alarm" refers to a notification or warning issued when an abnormality is detected. 【0263】 "Response measures" refer to the actions or measures to be taken in response to detected anomalies. 【0264】 A "report" refers to a document that summarizes analysis results, warnings, and countermeasures. 【0265】 A "user interface" refers to a screen or device that allows humans to operate and view the functions and information of a system. 【0266】 This invention describes an embodiment of a system that collects and analyzes environmental information in real time, detects anomalies, and provides appropriate countermeasures. First, a server controls environmental monitoring equipment and collects environmental information for a specific area using a group of sensors and unmanned aerial vehicles. This includes measuring temperature, humidity, and pollutant concentrations. The collected environmental information is transmitted to the server using wireless communication technology and stored in cloud storage. 【0267】 The server uses high-performance analytical algorithms and AI technology to analyze stored data. The AI ​​model predicts future environmental changes and natural disaster risks based on historical data. If an abnormal data pattern is detected, the server generates an alarm and sends it to the terminal in real time. 【0268】 When the device receives this alert, it uses a geographic information system to visualize environmental information, and the user makes a judgment based on this information. Specific countermeasures recommended on the device include refraining from going outside and wearing a filter mask. 【0269】 Furthermore, the server periodically integrates the analysis results and automatically generates environmental reports. These reports include historical data and forecast information, and are available to users in PDF and HTML formats. 【0270】 For example, if the concentration of carbon dioxide in the atmosphere rises sharply in a certain area, the server analyzes the data using an AI model and assesses the health risks. Based on this assessment, an alert is quickly sent to the terminal, and specific countermeasures are suggested to the user. 【0271】 An example of a prompt message for a generating AI model might be: "Based on carbon dioxide concentration data from the past 24 hours, predict future health risks and suggest countermeasures." 【0272】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0273】 Step 1: 【0274】 The server activates the sensor device and collects environmental information for a specified area. The input is raw data measured by the sensor (temperature, humidity, pollutant concentration, etc.). This data is transmitted to the server using wireless communication. The output is raw environmental data, which is stored in cloud storage. Specifically, the sensor periodically monitors the surrounding environment and transmits the data in real time. 【0275】 Step 2: 【0276】 The server processes raw data stored in the cloud using high-performance analytical algorithms. The input is unprocessed data stored in cloud storage. Data processing involves cleaning and analyzing the data using statistical methods and AI models. The output is analytical results based on comparisons with historical data. Specifically, the AI ​​model detects anomalous patterns and predicts future environmental changes and natural disaster risks. 【0277】 Step 3: 【0278】 The server generates an alarm if an anomaly is detected based on the analysis results. The input consists of data obtained in the analysis step and prediction results. The server processes this data to determine if an anomaly is present and creates an alarm if necessary. The output is an alarm message, which is sent to the terminal. Specifically, the alert is communicated to the user via email or app notifications. 【0279】 Step 4: 【0280】 The terminal visualizes the received alarms by utilizing a Geographic Information System (GIS). The inputs are the alarm messages and analysis results transmitted from the server. The GIS system processes this and provides an intuitive map display. As an output, the environmental situation on the map presented to the user is obtained. Specifically, the alarm levels and countermeasures for each region are displayed on the user's interface and provided in an easy-to-understand state. 【0281】 Step 5: 【0282】 Based on the presented information, the user takes appropriate countermeasures as needed. The inputs are the alarm information and map display obtained from the terminal. Based on this, the user determines specific actions. The output is the user's action plan. As specific actions, measures corresponding to the situation such as refraining from going out and wearing a filter mask are implemented. 【0283】 (Application Example 1) 【0284】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0285】 In modern society, environmental changes in urban areas directly affect the lives and health of citizens. However, conventional environmental monitoring devices have limited data collection, making it difficult to provide real-time predictions and alarms. Therefore, there is a problem that prompt and appropriate countermeasures cannot be taken against environmental changes. 【0286】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0287】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information within a cloud infrastructure, and means for visualizing the analyzed data as geographic information and displaying it on a mobile device. This enables citizens to check the environmental conditions around them at any time and take prompt action to prevent health damage. 【0288】 "Environmental monitoring equipment" refers to devices that collect environmental information such as temperature, humidity, and pollutant concentrations in a specific area. 【0289】 "Real-time" refers to processing and transmission of information at a time close to the moment it is generated. 【0290】 A "cloud infrastructure" is a distributed computing environment that provides data storage and computing processing over the internet. 【0291】 "Analysis" refers to methods and processes for revealing trends and characteristics in collected data. 【0292】 "Geographic information" refers to location data about specific points or regions, as well as related supplementary information. 【0293】 A "mobile device" is a portable communication device such as a mobile phone or tablet. 【0294】 "Citizen" refers to an ordinary individual residing in a particular region or city. 【0295】 "Health damage" refers to the potential for changes in the environment or living conditions to negatively affect a person's health. 【0296】 This invention is a system for smart cities that collects, analyzes, and visualizes environmental data in real time. The system consists of a server, terminals, and users. 【0297】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. This aggregates the environmental information, ensuring that the latest data is always stored within the cloud infrastructure. To process the collected data, the server executes high-performance analysis algorithms on the cloud infrastructure. For specific analyses, AI frameworks such as TensorFlow are used. 【0298】 The terminal is a mobile device such as a smartphone or tablet, and it presents information to the user through a mobile application based on analyzed data received from the server. Using geographic information systems such as Leaflet.js, the collected data can be displayed on an intuitive map. This allows users to visually understand the environmental conditions of their surrounding area. 【0299】 This system allows users to receive real-time alerts about environmental changes. These alerts include risks such as worsening air pollution and rising temperatures, and based on this, specific countermeasures (e.g., staying indoors, using a mask with a filter) are suggested. 【0300】 In generating a specific program, the following prompt can be used: "Based on the city's air pollution data for the past week, assess this week's forecast and potential health hazards, and suggest necessary preventative measures." This prompt allows the generated AI model to analyze the data and suggest countermeasures. 【0301】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0302】 Step 1: 【0303】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. The input is data from environmental sensors, and the output is transmitted to the cloud infrastructure. This data collection is automated, allowing for real-time, up-to-date information to be constantly maintained. 【0304】 Step 2: 【0305】 The server analyzes the data collected using TensorFlow on the cloud infrastructure. The input is the environmental data collected in Step 1, and the output is the analysis result detecting anomalies. In the analysis, a generative AI model is used to compare past data with current data to predict future environmental changes and disaster risks. 【0306】 Step 3: 【0307】 The server generates an alarm based on the analysis result and formulates specific countermeasures. The input is the analysis result of Step 2, and the output is the generated alarm and countermeasures. As a specific operation, when the system detects the progress of abnormal air pollution, it issues specific instructions for citizens to refrain from going out. 【0308】 Step 4: 【0309】 The terminal displays the analysis result and the alarm received from the server on the mobile device. The input is the alarm and countermeasures generated in Step 3, and the output is the information displayed on the user interface. Using Leaflet.js, the visualized map information is displayed on the terminal so that the user can intuitively understand it. 【0310】 Step 5: 【0311】 The user selects an appropriate action based on the information provided through the terminal. The input is the alarm and countermeasures displayed in Step 4, and the output is the user's specific action (e.g., refraining from going out). The user can make an appropriate judgment to prevent health damage based on the surrounding environmental information. 【0312】 Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion. 【0313】 This invention provides a system that combines environmental data collected by an environmental monitoring device with an emotion engine that recognizes user emotions, and provides warnings and countermeasures tailored to the user's emotions. The aim of this system is to improve the user experience and provide more personalized countermeasures. 【0314】 Specifically, the server collects environmental data using a sensor network and autonomous unmanned aerial vehicles. The collected data is analyzed in a cloud environment to predict environmental changes and disaster risks. Based on these analysis results, the server detects anomalies and generates alarms. 【0315】 Simultaneously, the emotion engine operates, and the device collects the user's voice data, facial expression data, and biometric data. The emotion engine analyzes this data to determine the user's emotional state. For example, it analyzes various emotional states, such as whether the user is stressed or relaxed. 【0316】 The server considers the analyzed emotional data and adjusts the alerts and responses in a way that is optimal for the user. For example, if the user is feeling stressed, the system will deliver the alert in a calm tone and suggest relaxing techniques as a response. 【0317】 This personalized information is delivered to the user through their device. The device uses a geographic information system to visualize the results of environmental analysis on a map, presenting the information in a way that the user can intuitively understand. In addition, messages are displayed that are tailored to the user's emotional state, and emotionally sensitive encouragement or warnings are added. 【0318】 Through this series of processes, the system can simultaneously perform environmental monitoring and provide psychological support to users, enabling better countermeasures and increased peace of mind. This achieves both environmental protection and improved user confidence. 【0319】 The following describes the processing flow. 【0320】 Step 1: 【0321】 The server issues commands to the sensor network and autonomous unmanned aerial vehicles to collect environmental data. The devices activate and collect data such as temperature, humidity, and air quality in the specified area. 【0322】 Step 2: 【0323】 The terminal receives real-time environmental data transmitted from sensors and unmanned aerial vehicles. This data is transferred wirelessly to a database in the cloud. 【0324】 Step 3: 【0325】 The server analyzes incoming data in a cloud environment. Large-scale data processing algorithms are used for analysis, including purification and normalization. Based on the analysis results, potential environmental changes and disaster risks are predicted using AI algorithms. 【0326】 Step 4: 【0327】 If the server detects an anomaly based on the collected environmental data, it immediately generates an alarm and prepares to warn the user. 【0328】 Step 5: 【0329】 The device captures the user's voice data, facial expressions, and biometric information and transmits it to the emotion engine. 【0330】 Step 6: 【0331】 The server uses an emotion engine to analyze the user's emotional data. An emotion analysis model is used to determine the user's emotional state, such as stress or relaxation. 【0332】 Step 7: 【0333】 The server adjusts alarm messages and responses based on the user's emotional state. It determines the message tone and content according to the user's stress level and psychological state, and creates alarm notifications. 【0334】 Step 8: 【0335】 The device displays tailored warning messages to the user and visualizes environmental conditions as geographical information. It also presents the user with recommended actions that include emotionally sensitive encouragement and warnings. 【0336】 Step 9: 【0337】 Users take action based on the information presented. By taking actions that take into account environmental conditions and their personal psychological state, they can effectively mitigate risks and alleviate psychological burden. 【0338】 (Example 2) 【0339】 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". 【0340】 This invention aims to solve the problem of providing more personalized information and psychological support by offering warnings and response measures that take into account the user's emotional state, in addition to predicting environmental changes and disaster risks. Conventional systems analyze environmental data, but they are insufficient in providing response measures that take into account the user's emotional state, resulting in problems where they are limited to mere warning notifications. 【0341】 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. 【0342】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information in a remote information processing environment, and means for collecting the user's voice, facial expressions, and biosignals and performing emotion analysis. This makes it possible to provide adaptive and personalized warnings and countermeasures according to the user's emotional state. 【0343】 "Environmental monitoring equipment" refers to devices and sensors used to collect environmental information, and which have the function of acquiring physical or chemical data in real time. 【0344】 A "remote information processing environment" is an environment that utilizes cloud-based computing resources used to collect, analyze, and store data. 【0345】 "Emotion analysis" is the process of evaluating and identifying a user's psychological state and emotions based on their voice, facial expressions, and biosignals. 【0346】 A "personalized alert" is warning information that is customized based on the individual user's emotional state and circumstances, and delivered in an appropriate format. 【0347】 "Adaptive and personalized responses" refer to methods that integrate and analyze environmental information and the user's emotional state to provide users with optimized behavioral guidelines and recommendations. 【0348】 The system in this invention mainly consists of environmental monitoring equipment, a server, and a terminal. The role of each element and how the invention is implemented are shown below. 【0349】 The server collects environmental information acquired in real time from environmental monitoring equipment. This equipment includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. This data is sent to a cloud computing platform (e.g., a typical cloud service provider), where machine learning algorithms are used for data analysis. This analysis predicts environmental changes and the risk of disasters. 【0350】 Simultaneously, the device collects the user's voice, facial expressions, and biosignals to perform emotion analysis. The device uses smartphones and wearable devices to acquire the user's voice data and biometric data such as heart rate. This data is analyzed in a remote information processing environment to determine the user's emotional state. 【0351】 Once the analysis results are obtained, the server integrates and analyzes the collected environmental information and user emotion data. Based on these results, personalized alerts and responses are generated and appropriately adjusted. For example, a user experiencing tension might receive an alert message in a calm tone along with recommendations for relaxation. 【0352】 Users receive visualizations of environmental information via geographic information systems provided through their devices, as well as messages that take their emotional state into consideration. For example, if an abnormal weather event occurs nearby, a message such as "Please move to a safe place immediately. We will support you so that you can act with peace of mind" will be displayed. This entire process provides users with a sense of security and offers better countermeasures against emerging environmental risks. 【0353】 An example of a prompt to input into the generation AI model would be: "Generate weather information notifications that take into account the user's emotional state. If the user is feeling anxious, add a calming message." This allows the system to deliver appropriate information based on the situation. 【0354】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0355】 Step 1: 【0356】 The server collects environmental information in real time from environmental monitoring equipment. This process includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. The environmental data, as input, is sent to the server and stored on a cloud computing platform. Specifically, the sensors periodically acquire data and upload it to the server using wireless communication technology. 【0357】 Step 2: 【0358】 The server analyzes the collected environmental data within a remote information processing environment. The environmental data, as input, is analyzed using machine learning algorithms, and the output predicts environmental fluctuations and disaster risks. Specifically, the data analysis leverages cloud-based processing power to detect anomalous data patterns and generate warnings for future risks. 【0359】 Step 3: 【0360】 The device collects the user's voice, facial expressions, and biosignals. This collection process primarily utilizes smartphones and wearable devices. Voice data and biosignal data, as input, are acquired by the device and transmitted to a server. Specifically, the device captures voice with a microphone, facial expressions with a camera, and measures heart rate with a biosensor. 【0361】 Step 4: 【0362】 The server analyzes voice, facial expression, and biosignal data sent from the user. This includes a process that uses a generative AI model to determine the user's emotional state. The input is voice and biosignal data, and the output is the user's emotional state (e.g., stress, exhilaration, relaxation). Specifically, individual emotional state tags are generated based on the analysis results. 【0363】 Step 5: 【0364】 The server integrates environmental information and user sentiment data to generate alarms and countermeasures. Inputs include predicted environmental change data and user sentiment data. From this, the server outputs personalized alarm messages and countermeasures. Specifically, if an abnormality alarm is required, the alarm message is constructed in a tone appropriate to the user's emotional state. 【0365】 Step 6: 【0366】 The terminal presents the user with generated alarms and countermeasures. Input consists of alarm data and countermeasures from the server. The terminal outputs and displays this information in a user-friendly format. Specifically, it visualizes the alarm message on the terminal screen and provides audio warnings as needed. Using a geographic information system, information related to the user's location is also displayed on a map. 【0367】 Through these steps, the system can monitor environmental changes in real time and provide users with the most appropriate and emotionally sensitive information. 【0368】 (Application Example 2) 【0369】 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 as the "terminal". 【0370】 Conventional environmental monitoring systems have struggled to provide warnings and countermeasures that take into account the user's psychological state, limiting their ability to improve the user experience and provide personalized countermeasures. Furthermore, the visualization of environmental data can sometimes be difficult to understand intuitively, and further improvements are needed. Therefore, the present invention aims to realize the provision of environmental information that responds to the user's emotions, thereby improving their sense of security and convenience. 【0371】 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. 【0372】 In this invention, the server includes means for immediately accumulating data from a device that acquires environmental information, means for analyzing the accumulated data in an information processing environment, and means for identifying the user's emotional state and providing personalized countermeasures along with warnings. This makes it possible to provide optimal environmental information and countermeasures according to the user's psychological state. 【0373】 A "device for acquiring environmental information" refers to a device used to instantly collect data on the surrounding environment. 【0374】 "Information processing environment" refers to a system that includes computing infrastructure and cloud services for analyzing accumulated data. 【0375】 "Emotional state" is an indicator that shows the user's psychological and physiological condition, and is information analyzed from voice and facial expression data. 【0376】 "Personalized solutions" refer to customized solutions and suggestions tailored to the user's emotional state. 【0377】 An "information display device" is a device that provides information to users visually, and includes smartphones and displays. 【0378】 A "sensor group" is a system composed of multiple sensors, and is a group of devices used to acquire various environmental data. 【0379】 An "autonomous aircraft" is an aircraft that has the ability to collect data while flying autonomously without a driver. 【0380】 "Biometric information" refers to data that indicates the user's physical condition, and includes things like heart rate and body temperature. 【0381】 To implement this invention, first, a device for acquiring environmental information is deployed. Environmental data such as temperature, humidity, noise, and air quality are collected using a group of sensors or an autonomous aircraft. The data from these devices is immediately transmitted to an information processing environment located in the cloud. 【0382】 The server processes the collected environmental data using advanced data analysis techniques. This analysis utilizes Google Cloud and TensorFlow, applying models to predict environmental changes and disaster risks. Based on the predicted results, if an anomaly is detected, an appropriate warning is generated and notified to the user. 【0383】 Meanwhile, the user's smartphone sends biometric information such as voice, heart rate, and facial expressions to an emotion analysis engine. This analysis uses an AI model based on TensorFlow to determine the user's emotional state in real time. For example, if the system determines that the user is feeling stressed, relaxation strategies are automatically selected. 【0384】 The user's device displays analysis results along with suggested actions and advice tailored to their emotional state. The information is visualized on a map and presented in an easy-to-understand format. For example, if the system determines the user is experiencing high stress, a message such as, "There's a relaxing park nearby. Why not stop by?" might be displayed. 【0385】 This system can provide users with optimal information and advice by inputting prompts into a generative AI model. An example of a prompt for the generative AI model would be, "Please tell me about nearby relaxation spots that I can use right now. The user is experiencing high stress." In this way, a system integrating environmental observation and emotion recognition can be realized, contributing to an improved user experience. 【0386】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0387】 Step 1: 【0388】 The server instantly receives environmental data such as temperature, humidity, noise, and air quality from devices that acquire environmental information. The input sensor data is sent to the cloud and aggregated on Google Cloud. This enables real-time environmental monitoring. 【0389】 Step 2: 【0390】 The server applies a data analysis model using TensorFlow to analyze the collected environmental data. Using the environmental data as input, it predicts environmental fluctuations and disaster risks, and generates a warning if an anomaly is detected. The output of this process is whether or not an anomaly was detected and the warning message. 【0391】 Step 3: 【0392】 The user's device sends biometric information such as voice, heart rate, and facial expression data to the emotion analysis engine. A TensorFlow AI model uses this data as input to analyze the user's emotional state. The output is the user's emotional state, such as "relaxed" or "highly stressed." 【0393】 Step 4: 【0394】 The server generates warnings and personalized responses based on analyzed emotional states and environmental data. It uses emotional states and environmental anomaly information as input, and prompts a generating AI model to determine the optimal advice. The output is a message displayed to the user. 【0395】 Step 5: 【0396】 The user's device uses the outputted message to utilize a geographic information system to visualize environmental information and countermeasures on a map. This makes it easy for users to intuitively check the information and implement countermeasures. Users can easily check detailed information and countermeasures by tapping on markers on the map. 【0397】 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. 【0398】 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. 【0399】 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. 【0400】 [Third Embodiment] 【0401】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0402】 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. 【0403】 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). 【0404】 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. 【0405】 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. 【0406】 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). 【0407】 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. 【0408】 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. 【0409】 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. 【0410】 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. 【0411】 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. 【0412】 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". 【0413】 This invention provides a system for collecting environmental data in real time by using a sensor network and an autonomous unmanned aerial vehicle as environmental observation devices. This system performs analysis in a cloud environment and enables AI-based prediction of environmental changes and disaster risks. Furthermore, it is designed to immediately issue an alarm and provide specific countermeasures if an anomaly is detected. 【0414】 Specifically, the server manages a sensor network and autonomous unmanned aerial vehicles for data collection. These devices measure temperature, humidity, pollutant concentrations, and other environmental data in specific areas. The collected data is transmitted to the server via wireless communication and stored in a cloud environment. 【0415】 The server utilizes high-performance analysis algorithms in the cloud to analyze the received environmental data. AI technology is used for data analysis, and by comparing it with historical data, it is possible to predict future environmental changes and disaster risks. For example, based on historical data, it is possible to predict the impact of air pollution in a specific area on health and to understand environmental changes in advance. 【0416】 If an anomaly is detected, an alert is sent to the device in real time. This allows users to quickly obtain information and take appropriate countermeasures. For example, if air pollution is worsening in a particular area, users will be advised to stay indoors or wear a filter mask. 【0417】 Furthermore, the terminal uses a geographic information system to visualize the collected data on a map. This visualization is important because it shows the environmental conditions of each region, making it easier for users to intuitively understand changes in the environment. 【0418】 Furthermore, this system automatically generates environmental reports periodically based on the analysis results. This allows users to comprehensively understand changes over time and utilize this information for long-term environmental conservation activities. For example, it can be used to monitor long-term temperature changes in a particular region and provide data for taking measures against climate change. 【0419】 By combining these features, this invention enables the efficient collection and analysis of environmental data, as well as prediction and response based on that data, thereby contributing to the realization of a sustainable global environment. 【0420】 The following describes the processing flow. 【0421】 Step 1: 【0422】 The server sends data collection commands to the sensor network and autonomous unmanned aerial vehicles. This activates each device, which then begins collecting environmental data in a pre-configured area. 【0423】 Step 2: 【0424】 The terminal receives real-time data transmitted from sensors and unmanned aerial vehicles. This includes information such as temperature, humidity, and pollutant concentrations. 【0425】 Step 3: 【0426】 The server sends the received data to a cloud environment where it is stored and initially analyzed. Data cleaning and normalization are performed to prepare the data for analysis. 【0427】 Step 4: 【0428】 The server uses AI algorithms to perform in-depth analysis on stored data. By comparing it with past data, it identifies patterns in environmental changes and predicts future fluctuations and anomalies. 【0429】 Step 5: 【0430】 Based on predictions made by the AI ​​model, the server detects anomalies. If an anomaly is identified, it quickly generates an alert and develops countermeasures according to the predicted risk level. 【0431】 Step 6: 【0432】 The terminal receives alarms and countermeasure information sent from the server. This allows the user to obtain this information in real time and take necessary actions immediately. 【0433】 Step 7: 【0434】 Users will take action based on the countermeasures provided. For example, they will follow instructions such as wearing a mask or closing windows in response to predicted air pollution. 【0435】 Step 8: 【0436】 The terminal visualizes the data analyzed by the system as geographical information. This allows users to intuitively understand the current environmental conditions and predicted changes on a map. 【0437】 Step 9: 【0438】 The server automatically generates and distributes weekly and monthly environmental reports to users on a regular basis. These reports include comparisons with historical data and trend analysis, which is helpful for considering long-term countermeasures. 【0439】 (Example 1) 【0440】 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." 【0441】 There is a need to rapidly and accurately predict risks from environmental changes and natural disasters, and to provide appropriate countermeasures. However, conventional environmental monitoring systems suffer from delays in data collection and analysis, resulting in insufficient real-time prediction and warning issuance. Furthermore, visualization for intuitive understanding of collected data and the presentation of concrete countermeasures are inadequate. Therefore, an efficient system that integrates environmental information collection, analysis, prediction, warning, and countermeasure provision is required. 【0442】 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. 【0443】 In this invention, the server includes means for collecting environmental information in real time from an environmental monitoring device, means for analyzing the collected environmental information within an information processing environment, and means for predicting environmental changes and natural disaster risks by comparing them with past data using a high-performance analysis algorithm. This enables efficient collection of environmental information and the provision of highly accurate future predictions, rapid warnings, and countermeasures. 【0444】 "Environmental monitoring equipment" refers to a system that includes sensors and devices for measuring and recording environmental information. 【0445】 "Real-time" refers to processing and analysis of information as close as possible to the moment it is collected. 【0446】 "Environmental information" refers to data related to the natural environment, such as temperature, humidity, and pollutant concentrations. 【0447】 An "information processing environment" refers to a computer system or cloud platform where data analysis, storage, and computational processing are performed. 【0448】 A "high-performance analysis algorithm" refers to a computational method used to process data efficiently and accurately and perform complex analyses. 【0449】 "Anomaly detection" refers to the process of identifying data or predictions that deviate from normal patterns. 【0450】 An "alarm" refers to a notification or warning issued when an abnormality is detected. 【0451】 "Response measures" refer to the actions or measures to be taken in response to detected anomalies. 【0452】 A "report" refers to a document that summarizes analysis results, warnings, and countermeasures. 【0453】 A "user interface" refers to a screen or device that allows humans to operate and view the functions and information of a system. 【0454】 This invention describes an embodiment of a system that collects and analyzes environmental information in real time, detects anomalies, and provides appropriate countermeasures. First, a server controls environmental monitoring equipment and collects environmental information for a specific area using a group of sensors and unmanned aerial vehicles. This includes measuring temperature, humidity, and pollutant concentrations. The collected environmental information is transmitted to the server using wireless communication technology and stored in cloud storage. 【0455】 The server uses high-performance analytical algorithms and AI technology to analyze stored data. The AI ​​model predicts future environmental changes and natural disaster risks based on historical data. If an abnormal data pattern is detected, the server generates an alarm and sends it to the terminal in real time. 【0456】 When the device receives this alert, it uses a geographic information system to visualize environmental information, and the user makes a judgment based on this information. Specific countermeasures recommended on the device include refraining from going outside and wearing a filter mask. 【0457】 Furthermore, the server periodically integrates the analysis results and automatically generates environmental reports. These reports include historical data and forecast information, and are available to users in PDF and HTML formats. 【0458】 For example, if the concentration of carbon dioxide in the atmosphere rises sharply in a certain area, the server analyzes the data using an AI model and assesses the health risks. Based on this assessment, an alert is quickly sent to the terminal, and specific countermeasures are suggested to the user. 【0459】 An example of a prompt message for a generating AI model might be: "Based on carbon dioxide concentration data from the past 24 hours, predict future health risks and suggest countermeasures." 【0460】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0461】 Step 1: 【0462】 The server activates the sensor device and collects environmental information for a specified area. The input is raw data measured by the sensor (temperature, humidity, pollutant concentration, etc.). This data is transmitted to the server using wireless communication. The output is raw environmental data, which is stored in cloud storage. Specifically, the sensor periodically monitors the surrounding environment and transmits the data in real time. 【0463】 Step 2: 【0464】 The server processes raw data stored in the cloud using high-performance analytical algorithms. The input is unprocessed data stored in cloud storage. Data processing involves cleaning and analyzing the data using statistical methods and AI models. The output is analytical results based on comparisons with historical data. Specifically, the AI ​​model detects anomalous patterns and predicts future environmental changes and natural disaster risks. 【0465】 Step 3: 【0466】 The server generates an alarm if an anomaly is detected based on the analysis results. The input consists of data obtained in the analysis step and prediction results. The server processes this data to determine if an anomaly is present and creates an alarm if necessary. The output is an alarm message, which is sent to the terminal. Specifically, the alert is communicated to the user via email or app notifications. 【0467】 Step 4: 【0468】 The terminal visualizes received alarms using a Geographic Information System (GIS). Inputs include alarm messages and analysis results sent from the server. The GIS system processes this data to create an intuitive map display. The output provides the user with a map showing the environmental conditions. Specifically, the user interface displays regional alarm levels and countermeasures in an easy-to-understand format. 【0469】 Step 5: 【0470】 The user takes appropriate action based on the information presented. Inputs include warning information and a map display from the device. Based on this, the user decides on specific actions. The output is the user's action plan. Specific actions include taking situation-appropriate measures such as staying indoors or wearing a filter mask. 【0471】 (Application Example 1) 【0472】 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." 【0473】 In modern society, environmental changes in urban areas directly impact the lives and health of citizens. However, conventional environmental monitoring devices have limited data collection capabilities, making it difficult to provide real-time predictions and warnings. This creates a challenge in taking swift and appropriate measures in response to environmental changes. 【0474】 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. 【0475】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information within a cloud infrastructure, and means for visualizing the analyzed data as geographic information and displaying it on a mobile device. This enables citizens to check the environmental conditions around them at any time and take prompt action to prevent health damage. 【0476】 "Environmental monitoring equipment" refers to devices that collect environmental information such as temperature, humidity, and pollutant concentrations in a specific area. 【0477】 "Real-time" refers to processing and transmission of information at a time close to the moment it is generated. 【0478】 A "cloud infrastructure" is a distributed computing environment that provides data storage and computing processing over the internet. 【0479】 "Analysis" refers to methods and processes for revealing trends and characteristics in collected data. 【0480】 "Geographic information" refers to location data about specific points or regions, as well as related supplementary information. 【0481】 A "mobile device" is a portable communication device such as a mobile phone or tablet. 【0482】 "Citizen" refers to an ordinary individual residing in a particular region or city. 【0483】 "Health damage" refers to the potential for changes in the environment or living conditions to negatively affect a person's health. 【0484】 This invention is a system for smart cities that collects, analyzes, and visualizes environmental data in real time. The system consists of a server, terminals, and users. 【0485】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. This aggregates the environmental information, ensuring that the latest data is always stored within the cloud infrastructure. To process the collected data, the server executes high-performance analysis algorithms on the cloud infrastructure. For specific analyses, AI frameworks such as TensorFlow are used. 【0486】 The terminal is a mobile device such as a smartphone or tablet, and it presents information to the user through a mobile application based on analyzed data received from the server. Using geographic information systems such as Leaflet.js, the collected data can be displayed on an intuitive map. This allows users to visually understand the environmental conditions of their surrounding area. 【0487】 This system allows users to receive real-time alerts about environmental changes. These alerts include risks such as worsening air pollution and rising temperatures, and based on this, specific countermeasures (e.g., staying indoors, using a mask with a filter) are suggested. 【0488】 In generating a specific program, the following prompt can be used: "Based on the city's air pollution data for the past week, assess this week's forecast and potential health hazards, and suggest necessary preventative measures." This prompt allows the generated AI model to analyze the data and suggest countermeasures. 【0489】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0490】 Step 1: 【0491】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. The input is data from environmental sensors, and the output is transmitted to the cloud infrastructure. This data collection is automated, allowing for real-time, up-to-date information to be constantly maintained. 【0492】 Step 2: 【0493】 The server analyzes data collected using TensorFlow on a cloud infrastructure. The input is environmental data collected in step 1, and the output is analysis results that detect anomalies. The analysis uses a generative AI model to compare past and present data and predict future environmental changes and disaster risks. 【0494】 Step 3: 【0495】 The server generates an alarm based on the analysis results and formulates specific countermeasures. The input is the analysis results from step 2, and the output is the generated alarm and countermeasures. Specifically, if the system detects the progression of abnormal air pollution, it issues specific instructions to citizens to refrain from going outside. 【0496】 Step 4: 【0497】 The terminal displays the analysis results and alarms received from the server on the mobile device. The input is the alarms and countermeasures generated in step 3, and the output is the information displayed on the user interface. Leaflet.js is used to display visualized map information on the terminal, making it easy for the user to understand intuitively. 【0498】 Step 5: 【0499】 The user selects an appropriate action based on the information provided through the device. The input is the warnings and countermeasures displayed in step 4, and the output is the user's specific action (e.g., refrain from going outside). Based on the surrounding environmental information, the user can make appropriate decisions to prevent health damage. 【0500】 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. 【0501】 This invention provides a system that combines environmental data collected by an environmental monitoring device with an emotion engine that recognizes user emotions, and provides warnings and countermeasures tailored to the user's emotions. The aim of this system is to improve the user experience and provide more personalized countermeasures. 【0502】 Specifically, the server collects environmental data using a sensor network and autonomous unmanned aerial vehicles. The collected data is analyzed in a cloud environment to predict environmental changes and disaster risks. Based on these analysis results, the server detects anomalies and generates alarms. 【0503】 Simultaneously, the emotion engine operates, and the device collects the user's voice data, facial expression data, and biometric data. The emotion engine analyzes this data to determine the user's emotional state. For example, it analyzes various emotional states, such as whether the user is stressed or relaxed. 【0504】 The server considers the analyzed emotional data and adjusts the alerts and responses in a way that is optimal for the user. For example, if the user is feeling stressed, the system will deliver the alert in a calm tone and suggest relaxing techniques as a response. 【0505】 This personalized information is delivered to the user through their device. The device uses a geographic information system to visualize the results of environmental analysis on a map, presenting the information in a way that the user can intuitively understand. In addition, messages are displayed that are tailored to the user's emotional state, and emotionally sensitive encouragement or warnings are added. 【0506】 Through this series of processes, the system can simultaneously perform environmental monitoring and provide psychological support to users, enabling better countermeasures and increased peace of mind. This achieves both environmental protection and improved user confidence. 【0507】 The following describes the processing flow. 【0508】 Step 1: 【0509】 The server issues commands to the sensor network and autonomous unmanned aerial vehicles to collect environmental data. The devices activate and collect data such as temperature, humidity, and air quality in the specified area. 【0510】 Step 2: 【0511】 The terminal receives real-time environmental data transmitted from sensors and unmanned aerial vehicles. This data is transferred wirelessly to a database in the cloud. 【0512】 Step 3: 【0513】 The server analyzes incoming data in a cloud environment. Large-scale data processing algorithms are used for analysis, including purification and normalization. Based on the analysis results, potential environmental changes and disaster risks are predicted using AI algorithms. 【0514】 Step 4: 【0515】 If the server detects an anomaly based on the collected environmental data, it immediately generates an alarm and prepares to warn the user. 【0516】 Step 5: 【0517】 The device captures the user's voice data, facial expressions, and biometric information and transmits it to the emotion engine. 【0518】 Step 6: 【0519】 The server uses an emotion engine to analyze the user's emotional data. An emotion analysis model is used to determine the user's emotional state, such as stress or relaxation. 【0520】 Step 7: 【0521】 The server adjusts alarm messages and responses based on the user's emotional state. It determines the message tone and content according to the user's stress level and psychological state, and creates alarm notifications. 【0522】 Step 8: 【0523】 The device displays tailored warning messages to the user and visualizes environmental conditions as geographical information. It also presents the user with recommended actions that include emotionally sensitive encouragement and warnings. 【0524】 Step 9: 【0525】 Users take action based on the information presented. By taking actions that take into account environmental conditions and their personal psychological state, they can effectively mitigate risks and alleviate psychological burden. 【0526】 (Example 2) 【0527】 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." 【0528】 This invention aims to solve the problem of providing more personalized information and psychological support by offering warnings and response measures that take into account the user's emotional state, in addition to predicting environmental changes and disaster risks. Conventional systems analyze environmental data, but they are insufficient in providing response measures that take into account the user's emotional state, resulting in problems where they are limited to mere warning notifications. 【0529】 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. 【0530】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information in a remote information processing environment, and means for collecting the user's voice, facial expressions, and biosignals and performing emotion analysis. This makes it possible to provide adaptive and personalized warnings and countermeasures according to the user's emotional state. 【0531】 "Environmental monitoring equipment" refers to devices and sensors used to collect environmental information, and which have the function of acquiring physical or chemical data in real time. 【0532】 A "remote information processing environment" is an environment that utilizes cloud-based computing resources used to collect, analyze, and store data. 【0533】 "Emotion analysis" is the process of evaluating and identifying a user's psychological state and emotions based on their voice, facial expressions, and biosignals. 【0534】 A "personalized alert" is warning information that is customized based on the individual user's emotional state and circumstances, and delivered in an appropriate format. 【0535】 "Adaptive and personalized responses" refer to methods that integrate and analyze environmental information and the user's emotional state to provide users with optimized behavioral guidelines and recommendations. 【0536】 The system in this invention mainly consists of environmental monitoring equipment, a server, and a terminal. The role of each element and how the invention is implemented are shown below. 【0537】 The server collects environmental information acquired in real time from environmental monitoring equipment. This equipment includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. This data is sent to a cloud computing platform (e.g., a typical cloud service provider), where machine learning algorithms are used for data analysis. This analysis predicts environmental changes and the risk of disasters. 【0538】 Simultaneously, the device collects the user's voice, facial expressions, and biosignals to perform emotion analysis. The device uses smartphones and wearable devices to acquire the user's voice data and biometric data such as heart rate. This data is analyzed in a remote information processing environment to determine the user's emotional state. 【0539】 Once the analysis results are obtained, the server integrates and analyzes the collected environmental information and user emotion data. Based on these results, personalized alerts and responses are generated and appropriately adjusted. For example, a user experiencing tension might receive an alert message in a calm tone along with recommendations for relaxation. 【0540】 Users receive visualizations of environmental information via geographic information systems provided through their devices, as well as messages that take their emotional state into consideration. For example, if an abnormal weather event occurs nearby, a message such as "Please move to a safe place immediately. We will support you so that you can act with peace of mind" will be displayed. This entire process provides users with a sense of security and offers better countermeasures against emerging environmental risks. 【0541】 An example of a prompt to input into the generation AI model would be: "Generate weather information notifications that take into account the user's emotional state. If the user is feeling anxious, add a calming message." This allows the system to deliver appropriate information based on the situation. 【0542】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0543】 Step 1: 【0544】 The server collects environmental information in real time from environmental monitoring equipment. This process includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. The environmental data, as input, is sent to the server and stored on a cloud computing platform. Specifically, the sensors periodically acquire data and upload it to the server using wireless communication technology. 【0545】 Step 2: 【0546】 The server analyzes the collected environmental data within a remote information processing environment. The environmental data, as input, is analyzed using machine learning algorithms, and the output predicts environmental fluctuations and disaster risks. Specifically, the data analysis leverages cloud-based processing power to detect anomalous data patterns and generate warnings for future risks. 【0547】 Step 3: 【0548】 The device collects the user's voice, facial expressions, and biosignals. This collection process primarily utilizes smartphones and wearable devices. Voice data and biosignal data, as input, are acquired by the device and transmitted to a server. Specifically, the device captures voice with a microphone, facial expressions with a camera, and measures heart rate with a biosensor. 【0549】 Step 4: 【0550】 The server analyzes voice, facial expression, and biosignal data sent from the user. This includes a process that uses a generative AI model to determine the user's emotional state. The input is voice and biosignal data, and the output is the user's emotional state (e.g., stress, exhilaration, relaxation). Specifically, individual emotional state tags are generated based on the analysis results. 【0551】 Step 5: 【0552】 The server integrates environmental information and user sentiment data to generate alarms and countermeasures. Inputs include predicted environmental change data and user sentiment data. From this, the server outputs personalized alarm messages and countermeasures. Specifically, if an abnormality alarm is required, the alarm message is constructed in a tone appropriate to the user's emotional state. 【0553】 Step 6: 【0554】 The terminal presents the user with generated alarms and countermeasures. Input consists of alarm data and countermeasures from the server. The terminal outputs and displays this information in a user-friendly format. Specifically, it visualizes the alarm message on the terminal screen and provides audio warnings as needed. Using a geographic information system, information related to the user's location is also displayed on a map. 【0555】 Through these steps, the system can monitor environmental changes in real time and provide users with the most appropriate and emotionally sensitive information. 【0556】 (Application Example 2) 【0557】 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." 【0558】 Conventional environmental monitoring systems have struggled to provide warnings and countermeasures that take into account the user's psychological state, limiting their ability to improve the user experience and provide personalized countermeasures. Furthermore, the visualization of environmental data can sometimes be difficult to understand intuitively, and further improvements are needed. Therefore, the present invention aims to realize the provision of environmental information that responds to the user's emotions, thereby improving their sense of security and convenience. 【0559】 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. 【0560】 In this invention, the server includes means for immediately accumulating data from a device that acquires environmental information, means for analyzing the accumulated data in an information processing environment, and means for identifying the user's emotional state and providing personalized countermeasures along with warnings. This makes it possible to provide optimal environmental information and countermeasures according to the user's psychological state. 【0561】 A "device for acquiring environmental information" refers to a device used to instantly collect data on the surrounding environment. 【0562】 "Information processing environment" refers to a system that includes computing infrastructure and cloud services for analyzing accumulated data. 【0563】 "Emotional state" is an indicator that shows the user's psychological and physiological condition, and is information analyzed from voice and facial expression data. 【0564】 "Personalized solutions" refer to customized solutions and suggestions tailored to the user's emotional state. 【0565】 An "information display device" is a device that provides information to users visually, and includes smartphones and displays. 【0566】 A "sensor group" is a system composed of multiple sensors, and is a group of devices used to acquire various environmental data. 【0567】 An "autonomous aircraft" is an aircraft that has the ability to collect data while flying autonomously without a driver. 【0568】 "Biometric information" refers to data that indicates the user's physical condition, and includes things like heart rate and body temperature. 【0569】 To implement this invention, first, a device for acquiring environmental information is deployed. Environmental data such as temperature, humidity, noise, and air quality are collected using a group of sensors or an autonomous aircraft. The data from these devices is immediately transmitted to an information processing environment located in the cloud. 【0570】 The server processes the collected environmental data using advanced data analysis techniques. This analysis utilizes Google Cloud and TensorFlow, applying models to predict environmental changes and disaster risks. Based on the predicted results, if an anomaly is detected, an appropriate warning is generated and notified to the user. 【0571】 Meanwhile, the user's smartphone sends biometric information such as voice, heart rate, and facial expressions to an emotion analysis engine. This analysis uses an AI model based on TensorFlow to determine the user's emotional state in real time. For example, if the system determines that the user is feeling stressed, relaxation strategies are automatically selected. 【0572】 The user's device displays analysis results along with suggested actions and advice tailored to their emotional state. The information is visualized on a map and presented in an easy-to-understand format. For example, if the system determines the user is experiencing high stress, a message such as, "There's a relaxing park nearby. Why not stop by?" might be displayed. 【0573】 This system can provide users with optimal information and advice by inputting prompts into a generative AI model. An example of a prompt for the generative AI model would be, "Please tell me about nearby relaxation spots that I can use right now. The user is experiencing high stress." In this way, a system integrating environmental observation and emotion recognition can be realized, contributing to an improved user experience. 【0574】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0575】 Step 1: 【0576】 The server instantly receives environmental data such as temperature, humidity, noise, and air quality from devices that acquire environmental information. The input sensor data is sent to the cloud and aggregated on Google Cloud. This enables real-time environmental monitoring. 【0577】 Step 2: 【0578】 The server applies a data analysis model using TensorFlow to analyze the collected environmental data. Using the environmental data as input, it predicts environmental fluctuations and disaster risks, and generates a warning if an anomaly is detected. The output of this process is whether or not an anomaly was detected and the warning message. 【0579】 Step 3: 【0580】 The user's device sends biometric information such as voice, heart rate, and facial expression data to the emotion analysis engine. A TensorFlow AI model uses this data as input to analyze the user's emotional state. The output is the user's emotional state, such as "relaxed" or "highly stressed." 【0581】 Step 4: 【0582】 The server generates warnings and personalized responses based on analyzed emotional states and environmental data. It uses emotional states and environmental anomaly information as input, and prompts a generating AI model to determine the optimal advice. The output is a message displayed to the user. 【0583】 Step 5: 【0584】 The user's device uses the outputted message to utilize a geographic information system to visualize environmental information and countermeasures on a map. This makes it easy for users to intuitively check the information and implement countermeasures. Users can easily check detailed information and countermeasures by tapping on markers on the map. 【0585】 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. 【0586】 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. 【0587】 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. 【0588】 [Fourth Embodiment] 【0589】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0590】 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. 【0591】 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). 【0592】 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. 【0593】 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. 【0594】 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). 【0595】 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. 【0596】 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. 【0597】 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. 【0598】 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. 【0599】 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. 【0600】 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. 【0601】 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". 【0602】 This invention provides a system for collecting environmental data in real time by using a sensor network and an autonomous unmanned aerial vehicle as environmental observation devices. This system performs analysis in a cloud environment and enables AI-based prediction of environmental changes and disaster risks. Furthermore, it is designed to immediately issue an alarm and provide specific countermeasures if an anomaly is detected. 【0603】 Specifically, the server manages a sensor network and autonomous unmanned aerial vehicles for data collection. These devices measure temperature, humidity, pollutant concentrations, and other environmental data in specific areas. The collected data is transmitted to the server via wireless communication and stored in a cloud environment. 【0604】 The server utilizes high-performance analysis algorithms in the cloud to analyze the received environmental data. AI technology is used for data analysis, and by comparing it with historical data, it is possible to predict future environmental changes and disaster risks. For example, based on historical data, it is possible to predict the impact of air pollution in a specific area on health and to understand environmental changes in advance. 【0605】 If an anomaly is detected, an alert is sent to the device in real time. This allows users to quickly obtain information and take appropriate countermeasures. For example, if air pollution is worsening in a particular area, users will be advised to stay indoors or wear a filter mask. 【0606】 Furthermore, the terminal uses a geographic information system to visualize the collected data on a map. This visualization is important because it shows the environmental conditions of each region, making it easier for users to intuitively understand changes in the environment. 【0607】 Furthermore, this system automatically generates environmental reports periodically based on the analysis results. This allows users to comprehensively understand changes over time and utilize this information for long-term environmental conservation activities. For example, it can be used to monitor long-term temperature changes in a particular region and provide data for taking measures against climate change. 【0608】 By combining these features, this invention enables the efficient collection and analysis of environmental data, as well as prediction and response based on that data, thereby contributing to the realization of a sustainable global environment. 【0609】 The following describes the processing flow. 【0610】 Step 1: 【0611】 The server sends data collection commands to the sensor network and autonomous unmanned aerial vehicles. This activates each device, which then begins collecting environmental data in a pre-configured area. 【0612】 Step 2: 【0613】 The terminal receives real-time data transmitted from sensors and unmanned aerial vehicles. This includes information such as temperature, humidity, and pollutant concentrations. 【0614】 Step 3: 【0615】 The server sends the received data to a cloud environment where it is stored and initially analyzed. Data cleaning and normalization are performed to prepare the data for analysis. 【0616】 Step 4: 【0617】 The server uses AI algorithms to perform in-depth analysis on stored data. By comparing it with past data, it identifies patterns in environmental changes and predicts future fluctuations and anomalies. 【0618】 Step 5: 【0619】 Based on predictions made by the AI ​​model, the server detects anomalies. If an anomaly is identified, it quickly generates an alert and develops countermeasures according to the predicted risk level. 【0620】 Step 6: 【0621】 The terminal receives alarms and countermeasure information sent from the server. This allows the user to obtain this information in real time and take necessary actions immediately. 【0622】 Step 7: 【0623】 Users will take action based on the countermeasures provided. For example, they will follow instructions such as wearing a mask or closing windows in response to predicted air pollution. 【0624】 Step 8: 【0625】 The terminal visualizes the data analyzed by the system as geographical information. This allows users to intuitively understand the current environmental conditions and predicted changes on a map. 【0626】 Step 9: 【0627】 The server automatically generates and distributes weekly and monthly environmental reports to users on a regular basis. These reports include comparisons with historical data and trend analysis, which is helpful for considering long-term countermeasures. 【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】 There is a need to rapidly and accurately predict risks from environmental changes and natural disasters, and to provide appropriate countermeasures. However, conventional environmental monitoring systems suffer from delays in data collection and analysis, resulting in insufficient real-time prediction and warning issuance. Furthermore, visualization for intuitive understanding of collected data and the presentation of concrete countermeasures are inadequate. Therefore, an efficient system that integrates environmental information collection, analysis, prediction, warning, and countermeasure provision is required. 【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 environmental information in real time from an environmental monitoring device, means for analyzing the collected environmental information within an information processing environment, and means for predicting environmental changes and natural disaster risks by comparing them with past data using a high-performance analysis algorithm. This enables efficient collection of environmental information and the provision of highly accurate future predictions, rapid warnings, and countermeasures. 【0633】 "Environmental monitoring equipment" refers to a system that includes sensors and devices for measuring and recording environmental information. 【0634】 "Real-time" refers to processing and analysis of information as close as possible to the moment it is collected. 【0635】 "Environmental information" refers to data related to the natural environment, such as temperature, humidity, and pollutant concentrations. 【0636】 An "information processing environment" refers to a computer system or cloud platform where data analysis, storage, and computational processing are performed. 【0637】 A "high-performance analysis algorithm" refers to a computational method used to process data efficiently and accurately and perform complex analyses. 【0638】 "Anomaly detection" refers to the process of identifying data or predictions that deviate from normal patterns. 【0639】 An "alarm" refers to a notification or warning issued when an abnormality is detected. 【0640】 "Response measures" refer to the actions or measures to be taken in response to detected anomalies. 【0641】 A "report" refers to a document that summarizes analysis results, warnings, and countermeasures. 【0642】 A "user interface" refers to a screen or device that allows humans to operate and view the functions and information of a system. 【0643】 This invention describes an embodiment of a system that collects and analyzes environmental information in real time, detects anomalies, and provides appropriate countermeasures. First, a server controls environmental monitoring equipment and collects environmental information for a specific area using a group of sensors and unmanned aerial vehicles. This includes measuring temperature, humidity, and pollutant concentrations. The collected environmental information is transmitted to the server using wireless communication technology and stored in cloud storage. 【0644】 The server uses high-performance analytical algorithms and AI technology to analyze stored data. The AI ​​model predicts future environmental changes and natural disaster risks based on historical data. If an abnormal data pattern is detected, the server generates an alarm and sends it to the terminal in real time. 【0645】 When the device receives this alert, it uses a geographic information system to visualize environmental information, and the user makes a judgment based on this information. Specific countermeasures recommended on the device include refraining from going outside and wearing a filter mask. 【0646】 Furthermore, the server periodically integrates the analysis results and automatically generates environmental reports. These reports include historical data and forecast information, and are available to users in PDF and HTML formats. 【0647】 For example, if the concentration of carbon dioxide in the atmosphere rises sharply in a certain area, the server analyzes the data using an AI model and assesses the health risks. Based on this assessment, an alert is quickly sent to the terminal, and specific countermeasures are suggested to the user. 【0648】 An example of a prompt message for a generating AI model might be: "Based on carbon dioxide concentration data from the past 24 hours, predict future health risks and suggest countermeasures." 【0649】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0650】 Step 1: 【0651】 The server activates the sensor device and collects environmental information for a specified area. The input is raw data measured by the sensor (temperature, humidity, pollutant concentration, etc.). This data is transmitted to the server using wireless communication. The output is raw environmental data, which is stored in cloud storage. Specifically, the sensor periodically monitors the surrounding environment and transmits the data in real time. 【0652】 Step 2: 【0653】 The server processes raw data stored in the cloud using high-performance analytical algorithms. The input is unprocessed data stored in cloud storage. Data processing involves cleaning and analyzing the data using statistical methods and AI models. The output is analytical results based on comparisons with historical data. Specifically, the AI ​​model detects anomalous patterns and predicts future environmental changes and natural disaster risks. 【0654】 Step 3: 【0655】 The server generates an alarm if an anomaly is detected based on the analysis results. The input consists of data obtained in the analysis step and prediction results. The server processes this data to determine if an anomaly is present and creates an alarm if necessary. The output is an alarm message, which is sent to the terminal. Specifically, the alert is communicated to the user via email or app notifications. 【0656】 Step 4: 【0657】 The terminal visualizes received alarms using a Geographic Information System (GIS). Inputs include alarm messages and analysis results sent from the server. The GIS system processes this data to create an intuitive map display. The output provides the user with a map showing the environmental conditions. Specifically, the user interface displays regional alarm levels and countermeasures in an easy-to-understand format. 【0658】 Step 5: 【0659】 The user takes appropriate action based on the information presented. Inputs include warning information and a map display from the device. Based on this, the user decides on specific actions. The output is the user's action plan. Specific actions include taking situation-appropriate measures such as staying indoors or wearing a filter mask. 【0660】 (Application Example 1) 【0661】 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". 【0662】 In modern society, environmental changes in urban areas directly impact the lives and health of citizens. However, conventional environmental monitoring devices have limited data collection capabilities, making it difficult to provide real-time predictions and warnings. This creates a challenge in taking swift and appropriate measures in response to environmental changes. 【0663】 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. 【0664】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information within a cloud infrastructure, and means for visualizing the analyzed data as geographic information and displaying it on a mobile device. This enables citizens to check the environmental conditions around them at any time and take prompt action to prevent health damage. 【0665】 "Environmental monitoring equipment" refers to devices that collect environmental information such as temperature, humidity, and pollutant concentrations in a specific area. 【0666】 "Real-time" refers to processing and transmission of information at a time close to the moment it is generated. 【0667】 A "cloud infrastructure" is a distributed computing environment that provides data storage and computing processing over the internet. 【0668】 "Analysis" refers to methods and processes for revealing trends and characteristics in collected data. 【0669】 "Geographic information" refers to location data about specific points or regions, as well as related supplementary information. 【0670】 A "mobile device" is a portable communication device such as a mobile phone or tablet. 【0671】 "Citizen" refers to an ordinary individual residing in a particular region or city. 【0672】 "Health damage" refers to the potential for changes in the environment or living conditions to negatively affect a person's health. 【0673】 This invention is a system for smart cities that collects, analyzes, and visualizes environmental data in real time. The system consists of a server, terminals, and users. 【0674】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. This aggregates the environmental information, ensuring that the latest data is always stored within the cloud infrastructure. To process the collected data, the server executes high-performance analysis algorithms on the cloud infrastructure. For specific analyses, AI frameworks such as TensorFlow are used. 【0675】 The terminal is a mobile device such as a smartphone or tablet, and it presents information to the user through a mobile application based on analyzed data received from the server. Using geographic information systems such as Leaflet.js, the collected data can be displayed on an intuitive map. This allows users to visually understand the environmental conditions of their surrounding area. 【0676】 This system allows users to receive real-time alerts about environmental changes. These alerts include risks such as worsening air pollution and rising temperatures, and based on this, specific countermeasures (e.g., staying indoors, using a mask with a filter) are suggested. 【0677】 In generating a specific program, the following prompt can be used: "Based on the city's air pollution data for the past week, assess this week's forecast and potential health hazards, and suggest necessary preventative measures." This prompt allows the generated AI model to analyze the data and suggest countermeasures. 【0678】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0679】 Step 1: 【0680】 The server collects environmental information such as temperature, humidity, and pollutant concentration from environmental monitoring equipment. The input is data from environmental sensors, and the output is transmitted to the cloud infrastructure. This data collection is automated, allowing for real-time, up-to-date information to be constantly maintained. 【0681】 Step 2: 【0682】 The server analyzes data collected using TensorFlow on a cloud infrastructure. The input is environmental data collected in step 1, and the output is analysis results that detect anomalies. The analysis uses a generative AI model to compare past and present data and predict future environmental changes and disaster risks. 【0683】 Step 3: 【0684】 The server generates an alarm based on the analysis results and formulates specific countermeasures. The input is the analysis results from step 2, and the output is the generated alarm and countermeasures. Specifically, if the system detects the progression of abnormal air pollution, it issues specific instructions to citizens to refrain from going outside. 【0685】 Step 4: 【0686】 The terminal displays the analysis results and alarms received from the server on the mobile device. The input is the alarms and countermeasures generated in step 3, and the output is the information displayed on the user interface. Leaflet.js is used to display visualized map information on the terminal, making it easy for the user to understand intuitively. 【0687】 Step 5: 【0688】 The user selects an appropriate action based on the information provided through the device. The input is the warnings and countermeasures displayed in step 4, and the output is the user's specific action (e.g., refrain from going outside). Based on the surrounding environmental information, the user can make appropriate decisions to prevent health damage. 【0689】 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. 【0690】 This invention provides a system that combines environmental data collected by an environmental monitoring device with an emotion engine that recognizes user emotions, and provides warnings and countermeasures tailored to the user's emotions. The aim of this system is to improve the user experience and provide more personalized countermeasures. 【0691】 Specifically, the server collects environmental data using a sensor network and autonomous unmanned aerial vehicles. The collected data is analyzed in a cloud environment to predict environmental changes and disaster risks. Based on these analysis results, the server detects anomalies and generates alarms. 【0692】 Simultaneously, the emotion engine operates, and the device collects the user's voice data, facial expression data, and biometric data. The emotion engine analyzes this data to determine the user's emotional state. For example, it analyzes various emotional states, such as whether the user is stressed or relaxed. 【0693】 The server considers the analyzed emotional data and adjusts the alerts and responses in a way that is optimal for the user. For example, if the user is feeling stressed, the system will deliver the alert in a calm tone and suggest relaxing techniques as a response. 【0694】 This personalized information is delivered to the user through their device. The device uses a geographic information system to visualize the results of environmental analysis on a map, presenting the information in a way that the user can intuitively understand. In addition, messages are displayed that are tailored to the user's emotional state, and emotionally sensitive encouragement or warnings are added. 【0695】 Through this series of processes, the system can simultaneously perform environmental monitoring and provide psychological support to users, enabling better countermeasures and increased peace of mind. This achieves both environmental protection and improved user confidence. 【0696】 The following describes the processing flow. 【0697】 Step 1: 【0698】 The server issues commands to the sensor network and autonomous unmanned aerial vehicles to collect environmental data. The devices activate and collect data such as temperature, humidity, and air quality in the specified area. 【0699】 Step 2: 【0700】 The terminal receives real-time environmental data transmitted from sensors and unmanned aerial vehicles. This data is transferred wirelessly to a database in the cloud. 【0701】 Step 3: 【0702】 The server analyzes incoming data in a cloud environment. Large-scale data processing algorithms are used for analysis, including purification and normalization. Based on the analysis results, potential environmental changes and disaster risks are predicted using AI algorithms. 【0703】 Step 4: 【0704】 If the server detects an anomaly based on the collected environmental data, it immediately generates an alarm and prepares to warn the user. 【0705】 Step 5: 【0706】 The device captures the user's voice data, facial expressions, and biometric information and transmits it to the emotion engine. 【0707】 Step 6: 【0708】 The server uses an emotion engine to analyze the user's emotional data. An emotion analysis model is used to determine the user's emotional state, such as stress or relaxation. 【0709】 Step 7: 【0710】 The server adjusts alarm messages and responses based on the user's emotional state. It determines the message tone and content according to the user's stress level and psychological state, and creates alarm notifications. 【0711】 Step 8: 【0712】 The device displays tailored warning messages to the user and visualizes environmental conditions as geographical information. It also presents the user with recommended actions that include emotionally sensitive encouragement and warnings. 【0713】 Step 9: 【0714】 Users take action based on the information presented. By taking actions that take into account environmental conditions and their personal psychological state, they can effectively mitigate risks and alleviate psychological burden. 【0715】 (Example 2) 【0716】 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". 【0717】 This invention aims to solve the problem of providing more personalized information and psychological support by offering warnings and response measures that take into account the user's emotional state, in addition to predicting environmental changes and disaster risks. Conventional systems analyze environmental data, but they are insufficient in providing response measures that take into account the user's emotional state, resulting in problems where they are limited to mere warning notifications. 【0718】 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. 【0719】 In this invention, the server includes means for collecting environmental information in real time from environmental monitoring equipment, means for analyzing the collected environmental information in a remote information processing environment, and means for collecting the user's voice, facial expressions, and biosignals and performing emotion analysis. This makes it possible to provide adaptive and personalized warnings and countermeasures according to the user's emotional state. 【0720】 "Environmental monitoring equipment" refers to devices and sensors used to collect environmental information, and which have the function of acquiring physical or chemical data in real time. 【0721】 A "remote information processing environment" is an environment that utilizes cloud-based computing resources used to collect, analyze, and store data. 【0722】 "Emotion analysis" is the process of evaluating and identifying a user's psychological state and emotions based on their voice, facial expressions, and biosignals. 【0723】 A "personalized alert" is warning information that is customized based on the individual user's emotional state and circumstances, and delivered in an appropriate format. 【0724】 "Adaptive and personalized responses" refer to methods that integrate and analyze environmental information and the user's emotional state to provide users with optimized behavioral guidelines and recommendations. 【0725】 The system in this invention mainly consists of environmental monitoring equipment, a server, and a terminal. The role of each element and how the invention is implemented are shown below. 【0726】 The server collects environmental information acquired in real time from environmental monitoring equipment. This equipment includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. This data is sent to a cloud computing platform (e.g., a typical cloud service provider), where machine learning algorithms are used for data analysis. This analysis predicts environmental changes and the risk of disasters. 【0727】 Simultaneously, the device collects the user's voice, facial expressions, and biosignals to perform emotion analysis. The device uses smartphones and wearable devices to acquire the user's voice data and biometric data such as heart rate. This data is analyzed in a remote information processing environment to determine the user's emotional state. 【0728】 Once the analysis results are obtained, the server integrates and analyzes the collected environmental information and user emotion data. Based on these results, personalized alerts and responses are generated and appropriately adjusted. For example, a user experiencing tension might receive an alert message in a calm tone along with recommendations for relaxation. 【0729】 Users receive visualizations of environmental information via geographic information systems provided through their devices, as well as messages that take their emotional state into consideration. For example, if an abnormal weather event occurs nearby, a message such as "Please move to a safe place immediately. We will support you so that you can act with peace of mind" will be displayed. This entire process provides users with a sense of security and offers better countermeasures against emerging environmental risks. 【0730】 An example of a prompt to input into the generation AI model would be: "Generate weather information notifications that take into account the user's emotional state. If the user is feeling anxious, add a calming message." This allows the system to deliver appropriate information based on the situation. 【0731】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0732】 Step 1: 【0733】 The server collects environmental information in real time from environmental monitoring equipment. This process includes sensors that measure temperature, humidity, wind speed, and atmospheric pressure. The environmental data, as input, is sent to the server and stored on a cloud computing platform. Specifically, the sensors periodically acquire data and upload it to the server using wireless communication technology. 【0734】 Step 2: 【0735】 The server analyzes the collected environmental data within a remote information processing environment. The environmental data, as input, is analyzed using machine learning algorithms, and the output predicts environmental fluctuations and disaster risks. Specifically, the data analysis leverages cloud-based processing power to detect anomalous data patterns and generate warnings for future risks. 【0736】 Step 3: 【0737】 The device collects the user's voice, facial expressions, and biosignals. This collection process primarily utilizes smartphones and wearable devices. Voice data and biosignal data, as input, are acquired by the device and transmitted to a server. Specifically, the device captures voice with a microphone, facial expressions with a camera, and measures heart rate with a biosensor. 【0738】 Step 4: 【0739】 The server analyzes voice, facial expression, and biosignal data sent from the user. This includes a process that uses a generative AI model to determine the user's emotional state. The input is voice and biosignal data, and the output is the user's emotional state (e.g., stress, exhilaration, relaxation). Specifically, individual emotional state tags are generated based on the analysis results. 【0740】 Step 5: 【0741】 The server integrates environmental information and user sentiment data to generate alarms and countermeasures. Inputs include predicted environmental change data and user sentiment data. From this, the server outputs personalized alarm messages and countermeasures. Specifically, if an abnormality alarm is required, the alarm message is constructed in a tone appropriate to the user's emotional state. 【0742】 Step 6: 【0743】 The terminal presents the user with generated alarms and countermeasures. Input consists of alarm data and countermeasures from the server. The terminal outputs and displays this information in a user-friendly format. Specifically, it visualizes the alarm message on the terminal screen and provides audio warnings as needed. Using a geographic information system, information related to the user's location is also displayed on a map. 【0744】 Through these steps, the system can monitor environmental changes in real time and provide users with the most appropriate and emotionally sensitive information. 【0745】 (Application Example 2) 【0746】 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". 【0747】 Conventional environmental monitoring systems have struggled to provide warnings and countermeasures that take into account the user's psychological state, limiting their ability to improve the user experience and provide personalized countermeasures. Furthermore, the visualization of environmental data can sometimes be difficult to understand intuitively, and further improvements are needed. Therefore, the present invention aims to realize the provision of environmental information that responds to the user's emotions, thereby improving their sense of security and convenience. 【0748】 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. 【0749】 In this invention, the server includes means for immediately accumulating data from a device that acquires environmental information, means for analyzing the accumulated data in an information processing environment, and means for identifying the user's emotional state and providing personalized countermeasures along with warnings. This makes it possible to provide optimal environmental information and countermeasures according to the user's psychological state. 【0750】 A "device for acquiring environmental information" refers to a device used to instantly collect data on the surrounding environment. 【0751】 "Information processing environment" refers to a system that includes computing infrastructure and cloud services for analyzing accumulated data. 【0752】 "Emotional state" is an indicator that shows the user's psychological and physiological condition, and is information analyzed from voice and facial expression data. 【0753】 "Personalized solutions" refer to customized solutions and suggestions tailored to the user's emotional state. 【0754】 An "information display device" is a device that provides information to users visually, and includes smartphones and displays. 【0755】 A "sensor group" is a system composed of multiple sensors, and is a group of devices used to acquire various environmental data. 【0756】 An "autonomous aircraft" is an aircraft that has the ability to collect data while flying autonomously without a driver. 【0757】 "Biometric information" refers to data that indicates the user's physical condition, and includes things like heart rate and body temperature. 【0758】 To implement this invention, first, a device for acquiring environmental information is deployed. Environmental data such as temperature, humidity, noise, and air quality are collected using a group of sensors or an autonomous aircraft. The data from these devices is immediately transmitted to an information processing environment located in the cloud. 【0759】 The server processes the collected environmental data using advanced data analysis techniques. This analysis utilizes Google Cloud and TensorFlow, applying models to predict environmental changes and disaster risks. Based on the predicted results, if an anomaly is detected, an appropriate warning is generated and notified to the user. 【0760】 Meanwhile, the user's smartphone sends biometric information such as voice, heart rate, and facial expressions to an emotion analysis engine. This analysis uses an AI model based on TensorFlow to determine the user's emotional state in real time. For example, if the system determines that the user is feeling stressed, relaxation strategies are automatically selected. 【0761】 The user's device displays analysis results along with suggested actions and advice tailored to their emotional state. The information is visualized on a map and presented in an easy-to-understand format. For example, if the system determines the user is experiencing high stress, a message such as, "There's a relaxing park nearby. Why not stop by?" might be displayed. 【0762】 This system can provide users with optimal information and advice by inputting prompts into a generative AI model. An example of a prompt for the generative AI model would be, "Please tell me about nearby relaxation spots that I can use right now. The user is experiencing high stress." In this way, a system integrating environmental observation and emotion recognition can be realized, contributing to an improved user experience. 【0763】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0764】 Step 1: 【0765】 The server instantly receives environmental data such as temperature, humidity, noise, and air quality from devices that acquire environmental information. The input sensor data is sent to the cloud and aggregated on Google Cloud. This enables real-time environmental monitoring. 【0766】 Step 2: 【0767】 The server applies a data analysis model using TensorFlow to analyze the collected environmental data. Using the environmental data as input, it predicts environmental fluctuations and disaster risks, and generates a warning if an anomaly is detected. The output of this process is whether or not an anomaly was detected and the warning message. 【0768】 Step 3: 【0769】 The user's device sends biometric information such as voice, heart rate, and facial expression data to the emotion analysis engine. A TensorFlow AI model uses this data as input to analyze the user's emotional state. The output is the user's emotional state, such as "relaxed" or "highly stressed." 【0770】 Step 4: 【0771】 The server generates warnings and personalized responses based on analyzed emotional states and environmental data. It uses emotional states and environmental anomaly information as input, and prompts a generating AI model to determine the optimal advice. The output is a message displayed to the user. 【0772】 Step 5: 【0773】 The user's device uses the outputted message to utilize a geographic information system to visualize environmental information and countermeasures on a map. This makes it easy for users to intuitively check the information and implement countermeasures. Users can easily check detailed information and countermeasures by tapping on markers on the map. 【0774】 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. 【0775】 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. 【0776】 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 robot 414. 【0777】 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. 【0778】 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. 【0779】 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. 【0780】 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. 【0781】 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. 【0782】 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." 【0783】 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. 【0784】 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. 【0785】 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. 【0786】 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. 【0787】 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. 【0788】 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. 【0789】 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 this memory. 【0790】 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. 【0791】 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. 【0792】 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. 【0793】 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. 【0794】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0795】 The following is further disclosed regarding the embodiments described above. 【0796】 (Claim 1) 【0797】 A means of collecting environmental data in real time from environmental monitoring equipment, 【0798】 A means for analyzing the aforementioned collected environmental data within a cloud environment, 【0799】 A means for predicting environmental changes and disaster risks based on the analyzed data, 【0800】 A means for detecting an anomaly and generating an alarm based on the aforementioned prediction, 【0801】 A means of providing specific countermeasures along with the aforementioned warning, 【0802】 A system that includes this. 【0803】 (Claim 2) 【0804】 The system according to claim 1, wherein the environmental observation device includes a network of numerous sensors and an autonomous unmanned aerial vehicle. 【0805】 (Claim 3) 【0806】 The system according to claim 1, further comprising an interface for visualizing and displaying the analyzed data as geographical information. 【0807】 "Example 1" 【0808】 (Claim 1) 【0809】 A means of collecting environmental information in real time from environmental monitoring equipment, 【0810】 Means for analyzing the collected environmental information within an information processing environment, 【0811】 A method for predicting environmental changes and natural disaster risks by comparing them with historical data using high-performance analytical algorithms, 【0812】 means for detecting anomalies and generating alarms based on the aforementioned predictions, 【0813】 Means for providing specific countermeasures in response to the aforementioned alarm, 【0814】 A means of automatically generating reports, 【0815】 Means for providing a user interface for displaying the aforementioned generated report, 【0816】 A system that includes this. 【0817】 (Claim 2) 【0818】 The system according to claim 1, wherein the environmental observation device includes a plurality of sensor groups and an unmanned aerial vehicle. 【0819】 (Claim 3) 【0820】 The system according to claim 1, comprising an interface for visualizing the analyzed information as location information and outputting and displaying it. 【0821】 "Application Example 1" 【0822】 (Claim 1) 【0823】 A means of collecting environmental information in real time from environmental monitoring equipment, 【0824】 A means for analyzing the collected environmental information within a cloud infrastructure, 【0825】 A means for predicting future environmental changes and disaster risks based on the analyzed data, 【0826】 A means for detecting an anomaly and generating an alarm based on the aforementioned prediction, 【0827】 A means of providing specific countermeasures along with the aforementioned warning, 【0828】 A means for visualizing the aforementioned data as geographic information and displaying it on a mobile device, 【0829】 A system that includes this. 【0830】 (Claim 2) 【0831】 The system according to claim 1, wherein the environmental observation equipment includes a network of numerous sensors and an autonomous unmanned aerial vehicle. 【0832】 (Claim 3) 【0833】 The system according to claim 1, comprising an interface that always displays the analyzed data in its most up-to-date state and provides citizens with guidelines to prevent health damage. 【0834】 "Example 2 of combining an emotion engine" 【0835】 (Claim 1) 【0836】 A means of collecting environmental information in real time from environmental monitoring equipment, 【0837】 Means for analyzing the collected environmental information within a remote information processing environment, 【0838】 A means for predicting environmental changes and disaster risks based on the analyzed information, 【0839】 A means for detecting an anomaly and generating an alarm based on the aforementioned prediction, 【0840】 A means of collecting user voice, facial expressions, and biosignals, and performing emotion analysis, 【0841】 A means for adjusting warnings and countermeasures based on the results of the aforementioned emotion analysis, 【0842】 A means of providing adaptive countermeasures along with the aforementioned alarm, 【0843】 A system that includes this. 【0844】 (Claim 2) 【0845】 The system according to claim 1, wherein the environmental observation equipment includes a network of numerous sensors and an autonomous flight device. 【0846】 (Claim 3) 【0847】 The system according to claim 1, further comprising an interface for visualizing and displaying the analyzed information as geographical information. 【0848】 "Application example 2 when combining with an emotional engine" 【0849】 (Claim 1) 【0850】 A means of immediately collecting data from a device that acquires environmental information, 【0851】 Means for analyzing the aforementioned accumulated data in an information processing environment, 【0852】 A means of predicting environmental changes and crises inferred from the analyzed data, 【0853】 A means for detecting anomalies and generating warnings based on the aforementioned prediction, 【0854】 A means to identify the user's emotional state and provide personalized responses along with warnings, 【0855】 A means for visually displaying the aforementioned data and emotion analysis results on an information display device is provided. 【0856】 A system that includes this. 【0857】 (Claim 2) 【0858】 The system according to claim 1, wherein the device for acquiring the environmental information includes a group of numerous sensors and an autonomous aircraft. 【0859】 (Claim 3) 【0860】 The system according to claim 1, comprising a tool for analyzing a user's biometric information and determining their emotional state. [Explanation of Symbols] 【0861】 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 of collecting environmental data in real time from environmental monitoring equipment, A means for analyzing the aforementioned collected environmental data within a cloud environment, A means for predicting environmental changes and disaster risks based on the analyzed data, A means for detecting an anomaly and generating an alarm based on the aforementioned prediction, A means of providing specific countermeasures along with the aforementioned warning, A system that includes this. [Claim 2] The system according to claim 1, wherein the environmental observation device includes a network of numerous sensors and an autonomous unmanned aerial vehicle. [Claim 3] The system according to claim 1, further comprising an interface for visualizing and displaying the analyzed data as geographical information.

Images