system

Abstract

We provide the system. [Solution] Data collection methods for gathering information from local residents, A data analysis tool for analyzing collected data in real time and generating an action plan, A means of sharing information to notify residents of the generated action plan, Language processing tools to support communication among residents, A resource mapping method for mapping and notifying about available personnel and resources, 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 many local communities, during disasters or in daily life, due to lack of information and insufficient cooperation among residents, it is difficult to respond quickly and appropriately. Also, with the progress of aging, insufficient support for isolated elderly people is a major issue. In these situations, it is required to deliver appropriate information to each resident and effectively build cooperative relationships in the region. 【Means for Solving the Problems】 【0005】 This invention provides a means for generating and notifying residents of appropriate action plans by collecting information from local residents and analyzing the data in real time. This enables residents to respond quickly and effectively during disasters and in their daily lives. Furthermore, by combining language processing functions that support communication among residents with functions that map available personnel and resources, it strengthens the community's mutual assistance environment. 【0006】 "Data collection means" refers to devices and methods for obtaining information from local residents, and is a system that collects various types of data using sensors and devices. 【0007】 A "data analysis tool" is a system that analyzes collected data to detect anomalies and trends, and has the function of evaluating the situation in real time and formulating action plans. 【0008】 "Information sharing methods" refer to means of communicating generated action plans and notices to residents, and are systems that provide information via smartphones and bulletin boards. 【0009】 "Language processing means" refers to natural language processing technologies that support communication among residents, and in particular, means for facilitating the exchange of information between multiple languages. 【0010】 "Resource mapping means" refers to a function that identifies and maps available personnel and resources, and promptly notifies residents of their availability as needed. [Brief explanation of the drawing] 【0011】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of 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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0012】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0013】 First, let's explain the terminology used in the following explanation. 【0014】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0015】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0016】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0017】 In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc. 【0018】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0019】 [First Embodiment] 【0020】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0021】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0022】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0023】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0024】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0025】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0026】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0027】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0028】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0029】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0030】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0031】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0032】 This invention is a system designed to enable local residents to respond quickly and appropriately to various challenges during disasters and in their daily lives. This system promotes community mutual assistance by analyzing information collected from residents, generating and sharing necessary action plans, and providing support to the community. 【0033】 The server receives information from local residents' devices and sensor devices using data collection methods. This information includes weather data, health data, disaster prevention-related information, etc., and is stored in a database on the server. 【0034】 The server analyzes the data accumulated by data analysis tools in real time. During this process, it uses predictive models and anomaly detection algorithms to quickly grasp the situation and automatically generate action plans as needed. These generated plans are then prioritized based on their importance and urgency. 【0035】 The terminal receives action plans and information sent from the server and displays them on the user's smartphone or on local bulletin boards. This information sharing method allows residents to take appropriate action. For example, when an evacuation order is issued, the terminal immediately sends a notification to the user. 【0036】 The device also supports communication among residents through language processing capabilities. Natural language processing technology translates messages into multiple languages, including foreign languages, facilitating smooth information exchange. 【0037】 Furthermore, the server uses resource mapping to identify available personnel and resources based on the collected information. This allows for rapid notification to local residents as needed, enabling the deployment of effective support activities. 【0038】 As a concrete example, consider a case where an evacuation advisory is issued due to heavy rain in a certain area. The server receives weather information through a data collection device and quickly evaluates it using a data analysis device. It then generates an action plan, including movement to a safe evacuation site, and notifies residents via terminals. At this time, a language processing device notifies residents in the appropriate language for those who speak multiple languages. In addition, a resource mapping device distributes information to help volunteers assist with the evacuation of the elderly. Through these processes, the entire community can cooperate and evacuate safely. 【0039】 The following describes the processing flow. 【0040】 Step 1: 【0041】 The server collects data from local residents' devices and sensors. Specifically, the server receives data via an API and stores weather information, residents' health status, and current disaster information in a database. 【0042】 Step 2: 【0043】 The server analyzes data in real time using data analysis tools. For example, if it detects a sudden change in temperature or abnormal health data, it prepares to generate an alert. 【0044】 Step 3: 【0045】 The server generates an action plan based on the analyzed results. Specifically, it determines whether an evacuation order should be issued and what kind of support is needed, and then formulates a plan to address each situation. 【0046】 Step 4: 【0047】 The device receives instructions from the server and notifies the user. For example, if an evacuation advisory is included, it displays an alert on the user's smartphone and provides information on evacuation routes and shelters. 【0048】 Step 5: 【0049】 The device uses language processing to translate messages between residents who speak different languages, facilitating smooth communication. For example, a Japanese notification can be translated into English and communicated to residents in the appropriate language. 【0050】 Step 6: 【0051】 The server uses resource mapping tools to identify available personnel and resources. If necessary, it notifies volunteers and medical staff of specific tasks to encourage a rapid response. 【0052】 Step 7: 【0053】 Users act based on the information they receive to ensure their safety. For example, when heading to a designated evacuation center, residents use route guidance displayed on their devices to navigate. 【0054】 (Example 1) 【0055】 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." 【0056】 In modern society, crisis management and rapid communication within local communities are crucial challenges. In particular, delays in information and inadequate responses during disasters can exacerbate damage. Furthermore, sharing information among residents with diverse linguistic and cultural backgrounds presents significant difficulties. In this context, effective and rapid information gathering, analysis, sharing, and resource utilization are essential. 【0057】 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. 【0058】 In this invention, the server includes data acquisition means for collecting data from members of the local community, data processing means for immediately analyzing the acquired data and generating action plans, and information distribution means for notifying members of the generated action plans. This makes it possible to quickly and accurately collect and analyze information and communicate action plans to members. Furthermore, by using natural language processing means, efficient information sharing among multilingual residents becomes possible, strengthening cooperation throughout the community. 【0059】 A "member of a local community" refers to an individual or family who resides in a specific geographical area and belongs to that community. 【0060】 "Data acquisition means" refers to devices and methods for collecting various types of information from members of a local community. 【0061】 "Data processing means" refers to processes or devices that analyze acquired data and generate necessary action procedures based on that information. 【0062】 "Information distribution means" refers to a system or device for notifying members of generated action procedures and providing them with appropriate information. 【0063】 "Natural language processing means" refers to technologies for interpreting multiple languages ​​and performing translation and semantic understanding. 【0064】 "Resource identification means" refers to a system for identifying available resources and personnel and for notifying them of that information. 【0065】 This system is designed to support information gathering and problem solving within local communities. The server operates in a cloud environment and collects data from terminals and various sensor devices used by members of the community. This data includes weather information, health information, and disaster prevention information. APIs and IoT devices are used as data acquisition methods. 【0066】 The server executes data processing measures to analyze the collected data, and the software used here includes machine learning algorithms and anomaly detection algorithms for running predictive models. This analysis assesses the current situation in the region and identifies potential risks. Then, using generative AI models, appropriate action plans are automatically generated. These action plans are compiled as a list of actionable tasks and notified to members through information distribution channels. 【0067】 The terminal receives action instructions and related information transmitted from the server and displays them on the user's smartphone or on local bulletin boards. The information is provided in a format that users can immediately act upon and includes specific evacuation routes and safety measures to be followed. The terminal also uses natural language processing to enable multilingual support. This facilitates the exchange of information among residents who speak multiple languages, thereby promoting smoother communication. 【0068】 Furthermore, the server utilizes resource identification tools to identify resources and personnel within the region and sends notifications as needed. This enables the effective mobilization of volunteers and professionals, allowing for swift and appropriate support activities to address the challenges facing the community. 【0069】 As a concrete example, when a disaster is predicted, the server quickly analyzes weather data and generates action plans suggesting evacuation routes. These plans are translated into multiple languages ​​and provided to users via mobile devices. An example of a prompt to be input into the generating AI model is, "Generate the optimal action plan for the predicted disaster risk." This enables the entire community to cooperate and respond appropriately, minimizing damage. 【0070】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0071】 Step 1: 【0072】 The server collects information from terminals and sensor devices of each member of the community. Input data includes weather data, health data, and disaster prevention-related data. The server acquires this information in real time through data acquisition methods and stores it in a database. This data is then formatted and validated in preparation for subsequent analysis. 【0073】 Step 2: 【0074】 The server analyzes the collected data using data processing tools. It uses information stored in a database as input data. In the specific analysis, machine learning models and anomaly detection algorithms are employed, and as a result, evacuation advisories and health risk predictions are output. This process highlights anomalies and unique trends in the information, and action plans are generated based on this. 【0075】 Step 3: 【0076】 The server uses a generative AI model to generate action plans based on the analysis results. The analysis results from step 2 are used as input. The generated action plans include specific evacuation routes and recommended actions, and the generative AI model provides appropriate output when prompted with the message "Create the optimal action plan based on the current situation." 【0077】 Step 4: 【0078】 The terminal receives action instructions sent from the server and notifies members using an information distribution method. In this step, the generated action instructions are displayed on the user's mobile device or local bulletin board. The input is action instruction data from the server, and the output is provided as visual notifications or alerts. Users review this and take timely action according to their situation. 【0079】 Step 5: 【0080】 The terminal uses natural language processing to translate instructions and information into multiple languages. The input includes instructions received from the server, which are translated appropriately according to each member's language settings. This output enables smooth information sharing among residents who speak different languages, allowing all users to properly understand the instructions. 【0081】 Step 6: 【0082】 The server utilizes resource identification tools to identify local resources and available personnel. The input consists of collected data and analysis results. The output includes sending instructions and notifications for support activities to volunteers and professionals, enabling a rapid response across the region. 【0083】 (Application Example 1) 【0084】 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." 【0085】 In local communities, there is a need for rapid evacuation guidance during disasters and efficient provision of local information in daily life. Furthermore, promoting communication among residents and optimizing resource utilization are also important issues. However, this information is not provided in real time, and there is a lack of appropriate evacuation route guidance and multilingual support. Therefore, there is a growing need for systems that enable local residents to respond safely and appropriately. 【0086】 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. 【0087】 In this invention, the server includes information acquisition means for obtaining data from local residents, information analysis means for analyzing the acquired data with temporal realism and creating an action plan, information provision means for presenting the created action plan to local residents, language conversion means for supporting dialogue among residents, resource identification means for identifying and presenting available personnel and resources, and navigation application means for providing users with emergency evacuation routes and local information for normal times. This enables local residents to evacuate quickly during disasters and to use information efficiently in their daily lives. 【0088】 "Local residents" refers to individuals or households who live in a specific area and whose lives are affected by that area. 【0089】 "Information acquisition means" refers to devices and methods for collecting data from local residents, and includes collection processes using sensors and smart devices. 【0090】 "Information analysis means" refers to methods and technologies for processing collected data in real time, evaluating the situation, and deriving appropriate action plans. 【0091】 "Information provision means" refers to methods and devices for clearly notifying local residents of action plans and important information, and includes smartphones and digital bulletin boards. 【0092】 "Language translation means" refers to technologies and methods for translating messages in order to facilitate communication among local residents using diverse languages. 【0093】 "Resource identification methods" refer to technologies and techniques that identify human resources and material resources that can cooperate within a region, and provide information to efficiently utilize them. 【0094】 "Navigation application means" refers to technologies and devices that provide users with evacuation routes in emergencies and local information during normal times, supporting quick and appropriate action. 【0095】 This invention provides a system for effectively collecting, analyzing, and providing information within a local community. This system is implemented with a core configuration consisting of a server, terminals, and users. 【0096】 The server collects data from local residents using various data acquisition methods. This data includes various information such as location, weather conditions, and health status. The collected data is stored in databases such as AWS® RDS. The server performs real-time data analysis using data analysis tools such as TENSORFLOW® and Scikit-learn. Based on the analysis results, an appropriate action plan is automatically generated. 【0097】 The device, developed with React Native, functions as an information delivery tool. It displays action plans in multiple languages ​​on the user's smart device and instantly guides users to evacuation routes in emergencies. In normal times, it provides information on local events and commercial facilities, enriching the lives of local residents. 【0098】 Users access information provided by the system using smartphones and other devices. Especially in emergencies, they can respond quickly based on notifications from their devices to ensure their safety. 【0099】 As a concrete example, consider a scenario where a disaster occurs in a region. The server analyzes weather information in real time and generates an evacuation plan. The terminal notifies the user in multiple languages ​​and suggests appropriate evacuation routes. To facilitate this process, prompt statements are used as input to the generating AI model. A prompt statement such as, "Create a script that generates a rapid evacuation plan and notifies residents when a disaster occurs in the region," might be used. 【0100】 This system will enable local residents to obtain and effectively utilize necessary information in a timely manner during disasters and in their daily lives. 【0101】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0102】 Step 1: 【0103】 The server uses information acquisition methods to collect data from local residents' smart devices and sensors. The input data includes location information, weather information, and health data, which are identified, organized, and stored in AWS RDS. The output is an organized dataset. 【0104】 Step 2: 【0105】 The server uses TensorFlow as its data analysis tool to analyze stored data in real time. Through this analysis, algorithms are applied to detect anomalies and emergencies, and action plans necessary for residents are generated. The input is a well-organized dataset, and the output consists of action plans and anomaly detection results. 【0106】 Step 3: 【0107】 The server utilizes a generation AI model to generate necessary evacuation plans and action guidelines based on prompt messages. Prompt messages are in the format of "Please create a script to generate a rapid evacuation plan and notify residents." Input consists of analyzed data and prompt messages, while output is a specific evacuation plan. 【0108】 Step 4: 【0109】 The terminal notifies residents of action plans via information delivery methods on their smart devices. The notifications are multilingual and, in emergencies, can be immediately conveyed via voice or push notifications. The input is the action plan sent from the server, and the output is the notification displayed on the user's device. 【0110】 Step 5: 【0111】 Users take swift and accurate action based on information received from their devices. This includes specific actions such as following evacuation routes displayed on their smart devices or utilizing everyday information. The input is notifications from the device, and the output is the user's actual actions. 【0112】 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. 【0113】 This invention is a system that recognizes the emotional state of local residents and, based on that, provides appropriate action plans and information notifications. By combining this system with an emotion engine, it aims to add a new dimension to existing data collection, analysis, and notification processes, enabling residents to take quicker action with greater confidence. 【0114】 The server collects data from local residents' devices and sensor devices, including information for recognizing emotions such as voice data and biometric data. Using voice recognition technology and facial expression analysis, the emotion engine analyzes this data. Through this analysis, the server identifies the emotions a user is feeling in response to their situation. For example, if a resident is feeling anxious, this emotion can be used as a trigger to adjust the action plan accordingly. 【0115】 Based on the emotional states identified by the emotion engine, the server adjusts the action plan it generates. Specifically, it sends reassuring notifications to areas experiencing high levels of anxiety and, if necessary, suggests providing psychological care. When an evacuation order is issued, the server generates a notification that provides detailed instructions and support information based on the emotion analysis. 【0116】 The device receives and displays notifications tailored to each individual user, sent from the server. Depending on the user's emotions, the notification language may be softened, and information may be made visually easier to understand using illustrations and videos. For example, during an evacuation, it may provide calming messages to reduce fear and anxiety, and detailed information about the support system at the evacuation center. 【0117】 Furthermore, users can provide emotional feedback regarding questions and concerns via their devices. This information is analyzed by an emotion engine and used to improve the quality of services provided by the server. Additionally, language processing tools are adjusted based on emotions to support more effective communication among residents. 【0118】 In this way, the system of the present invention aims to improve the safety and sense of security of the entire community through flexible information provision and action plans that respond to the feelings of local residents. 【0119】 The following describes the processing flow. 【0120】 Step 1: 【0121】 The server collects data from local residents' devices and sensor equipment. This data includes voice and biosensor information and is stored in a database for analysis by the emotion engine. 【0122】 Step 2: 【0123】 The server analyzes collected voice and biometric data using an emotion engine. The emotion engine identifies the user's emotions from changes in voice tone, facial expressions, and heart rate. Examples of emotions include anxiety, anger, and relief. 【0124】 Step 3: 【0125】 The server integrates emotional information obtained from the emotion engine with existing data and performs real-time analysis. This analysis generates appropriate action plans for users with specific emotional states. 【0126】 Step 4: 【0127】 The generated action plan is fine-tuned to match the user's emotional state. For example, for anxious users, notifications and guidelines designed to promote a sense of security are incorporated. 【0128】 Step 5: 【0129】 The device receives personalized notifications sent from the server. The content of the notifications varies depending on the user's emotional state and is presented to the user at an appropriate time and with appropriate language. 【0130】 Step 6: 【0131】 Users receive notifications via their devices and act accordingly. These notifications include messages to alleviate anxiety and detailed evacuation procedures, which users refer to to ensure their safety. 【0132】 Step 7: 【0133】 The emotional feedback provided by users is sent back to the server and analyzed by the emotion engine. The results of this analysis are used to improve future services and optimize action plans. 【0134】 (Example 2) 【0135】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0136】 In local communities, there is a lack of means to quickly and accurately grasp the emotional state of residents and to develop appropriate action plans and provide information based on that understanding. This creates a problem where residents have difficulty ensuring their safety and sense of security during emergencies and in their daily lives. Furthermore, there are insufficient mechanisms for effective communication among residents and for using feedback to improve services. 【0137】 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. 【0138】 In this invention, the server includes an information receiving means, an emotion recognition means, a plan generation means, an information distribution means, and an opinion collection means. This enables the formulation of action plans and information provision in accordance with the emotional state of residents, and continuous improvement of services using feedback. 【0139】 "Information receiving means" refers to a device or method for collecting data such as voice data and biometric information from people in a local area. 【0140】 "Emotion recognition means" refers to a device or method for analyzing collected data and identifying residents' emotions using speech recognition technology or facial expression analysis technology. 【0141】 "Plan generation means" refers to a device or method for formulating an appropriate action plan based on the emotional state identified by the emotion recognition means. 【0142】 "Information distribution means" refers to a device or method for transmitting a formulated action plan as a notification to people's terminals and providing necessary information. 【0143】 "Means of collecting opinions" refers to devices or methods for collecting feedback from residents and using it to improve the system. 【0144】 This invention is a system that recognizes the emotional state of people in a region in real time and provides action plans and information notifications based on that recognition. This system operates with a server at its core, working in conjunction with terminals and various sensors. 【0145】 The server receives information collected from local residents. Data collected from terminals and sensor devices includes voice data and biometric information. Voice data is acquired using the terminal's microphone, and biometric information is acquired from wearable devices such as smartwatches and smart bands. This data is aggregated on the server and analyzed using voice recognition software and facial expression analysis algorithms. Specifically, "Google® Speech-to-Text API" and "Microsoft® Azure® Speech Service" can be used for voice recognition, and "OpenCV" can be used for facial expression analysis. 【0146】 The emotion recognition engine identifies people's emotional states based on these analysis results. For example, it can detect stress and anxiety from changes in voice tone and biometric information. Based on this emotional state, the server uses a generative AI model to formulate an action plan. Specifically, it creates messages to provide reassurance and provides information on evacuation routes and psychological care when needed. 【0147】 The device visually displays notifications sent from the server to users. These notifications include soft language, illustrations, and videos tailored to the user's emotional state, designed for intuitive understanding. For example, during an evacuation advisory, a calming message is displayed to alleviate fear, along with detailed information about evacuation shelters. 【0148】 Furthermore, users can send feedback to the server through their devices. This feedback is used to improve the system's performance. For example, prompts such as, "Please tell us how you are feeling right now. This information will help us improve the service," can be displayed. An example of a prompt might be, "Analyze how local residents are feeling about the disaster and generate notifications to encourage evacuation accordingly. These notifications should include reassuring messages and detailed information about evacuation shelters." 【0149】 In this way, the system of the present invention improves safety and security in local communities. 【0150】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0151】 Step 1: 【0152】 The server collects voice data and biometric information from terminals and sensor devices. Inputs include voice data obtained from the terminal's microphone and biometric information such as heart rate and skin temperature collected from wearable devices. This data is aggregated on the server and prepared for emotion analysis. 【0153】 Step 2: 【0154】 The server performs emotion recognition based on the collected data. The input consists of voice data and biometric information collected in step 1. The server analyzes this data using voice recognition software and facial expression analysis algorithms. For example, it analyzes voice tone to determine stress levels or observes changes in heart rate to infer feelings of anxiety. The output identifies the emotional state of the residents (e.g., reassured, stressed, anxious). 【0155】 Step 3: 【0156】 The server generates an action plan based on the identified emotional state. The input is the emotional state data from step 2. The server utilizes a generative AI model to analyze what information and actions residents need and formulate an appropriate action plan. For example, if it determines that a person is feeling anxious, it will create a message to provide reassurance. The output will be an action plan and notification messages. 【0157】 Step 4: 【0158】 The server adjusts the information notification based on the generated action plan and sends it to the terminal. The input is the notification message generated in step 3. The server adjusts the notification content to suit the residents' sentiments and makes it visually easy to understand. For example, it may include illustrations or videos to make the information easier to receive. The output is the adjusted notification sent to the residents' terminals. 【0159】 Step 5: 【0160】 The terminal displays notifications received from the server to the user. The input is the notification message sent in step 4. The terminal displays the notification in the user interface, using, for example, gentle colors and animations to alleviate anxiety. The output is the visual notification information received by the user. 【0161】 Step 6: 【0162】 Users provide feedback and send it to the server. Input consists of the user's emotions and responses to notifications. Users submit comments and feedback using the feedback function configured on their device. The server receives this feedback data and uses it to plan future actions and improve the service. Output is data for more refined sentiment analysis and service improvement. 【0163】 (Application Example 2) 【0164】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0165】 In modern urban environments, accurately understanding the emotional state of local residents and responding quickly and appropriately is essential. However, existing systems fail to adequately provide emotion-based action plans and information dissemination, hindering the creation of safe and secure cities. In particular, when residents' anxiety and fear escalate, delays in appropriate responses can lead to social unrest. To address these challenges, a system is needed that recognizes residents' emotional states in real time and provides corresponding response measures. 【0166】 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. 【0167】 In this invention, the server includes information gathering means for collecting information from local groups, information analysis means for analyzing the collected information in real time and creating an action plan, and emotion recognition means for recognizing emotional states and providing a sense of security. This enables flexible information provision and action planning based on the emotions of residents. 【0168】 "Information gathering methods" refer to methods for obtaining diverse forms of data from local groups. 【0169】 "Information analysis means" refers to a method for generating action plans by performing real-time analysis based on collected data. 【0170】 "Information transmission methods" refer to methods for effectively communicating created action plans and related information to a group. 【0171】 "Language processing means" refers to methods related to language processing that support communication between groups and effectively convey information. 【0172】 "Resource allocation means" refers to methods for optimally allocating available personnel and resources and notifying the group accordingly. 【0173】 "Emotion recognition methods" are techniques for identifying residents' emotional states and providing them with a sense of security. 【0174】 The system for realizing this invention mainly consists of a server, terminals, and users. The server acquires diverse data from local groups using information gathering means. Specifically, it utilizes hardware that collects voice and facial expression data through smartphones and sensor devices. This makes it possible to obtain detailed information about the emotional state of local residents. 【0175】 Next, the server processes and analyzes the collected data in real time using information analysis tools. This process utilizes cloud services and speech recognition technologies (e.g., Google Cloud Speech-to-Text and OpenCV). The analyzed data is then used to evaluate the emotional state of residents using emotion recognition tools, and an action plan is generated based on this evaluation. A key feature of this action plan is that it enables flexible information suggestions tailored to individual emotions. 【0176】 The generated action plan is communicated to the user via a terminal using an information transmission method. The display on the terminal incorporates emotionally-based message adjustments, and visual information is used to promote a sense of security among residents. For example, a smartphone application might be used to display text with soft language and illustrations in gentle colors. 【0177】 Furthermore, user feedback is sent to the server via the user's device. This information is analyzed by language processing tools to improve future services. Additionally, residents can feel a sense of security and support when providing feedback about their emotions. 【0178】 As a concrete example, if residents experience stress during an event in a certain area, the server will quickly recognize this emotion and generate a prompt message suggesting the event organizers to introduce a relaxation space. The system might propose a prompt message such as, "Based on the emotional data collected from event participants in this area, please evaluate the emotional state of the residents and consider countermeasures to provide them with a sense of security." 【0179】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0180】 Step 1: 【0181】 The server uses information gathering tools to acquire voice and facial expression data from local communities via smartphones and sensor devices. Inputs include real-time voice and image data transmitted from various devices. By collecting this data, the server can prepare a dataset that reflects the environment and emotional state of local residents. 【0182】 Step 2: 【0183】 The server processes the acquired audio and facial expression data in real time using information analysis tools. It utilizes Google Cloud Speech-to-Text to convert audio data into text data. It also uses OpenCV to analyze facial expression images and extract emotional parameters. The input consists of audio and image data, and the output is data indicating emotional states. This process generates foundational data for identifying the emotional states of residents. 【0184】 Step 3: 【0185】 The server evaluates the analyzed data using emotion recognition tools and identifies the emotional state of the residents. Using a generative AI model, it analyzes the emotional data from multiple perspectives and generates an action plan that reflects the current situation in the region. The input is emotional parameters, and the output is an action plan corresponding to those emotions. This step allows us to understand what kind of response the residents of the region need. 【0186】 Step 4: 【0187】 The server notifies the group of the generated action plan via an information transmission mechanism. The terminal receives the notification and displays a message on the screen in a soft tone that matches the user's emotions. For example, in addition to text messages, illustrations with calming colors are used. The input is the action plan, and the output is in the form of a screen display on the terminal. This notification gives the user a sense of security. 【0188】 Step 5: 【0189】 Users send feedback to the server via their devices. The server analyzes this information using language processing tools to improve future services. The input is user feedback data, and the output is an action plan for service improvement. Specifically, residents provide feedback after events, which is then used to plan future events. 【0190】 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. 【0191】 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. 【0192】 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. 【0193】 [Second Embodiment] 【0194】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0195】 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. 【0196】 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). 【0197】 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. 【0198】 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. 【0199】 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). 【0200】 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. 【0201】 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. 【0202】 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. 【0203】 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. 【0204】 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. 【0205】 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". 【0206】 This invention is a system designed to enable local residents to respond quickly and appropriately to various challenges during disasters and in their daily lives. This system promotes community mutual assistance by analyzing information collected from residents, generating and sharing necessary action plans, and providing support to the community. 【0207】 The server receives information from local residents' devices and sensor devices using data collection methods. This information includes weather data, health data, disaster prevention-related information, etc., and is stored in a database on the server. 【0208】 The server analyzes the data accumulated by data analysis tools in real time. During this process, it uses predictive models and anomaly detection algorithms to quickly grasp the situation and automatically generate action plans as needed. These generated plans are then prioritized based on their importance and urgency. 【0209】 The terminal receives action plans and information sent from the server and displays them on the user's smartphone or on local bulletin boards. This information sharing method allows residents to take appropriate action. For example, when an evacuation order is issued, the terminal immediately sends a notification to the user. 【0210】 The device also supports communication among residents through language processing capabilities. Natural language processing technology translates messages into multiple languages, including foreign languages, facilitating smooth information exchange. 【0211】 Furthermore, the server uses resource mapping to identify available personnel and resources based on the collected information. This allows for rapid notification to local residents as needed, enabling the deployment of effective support activities. 【0212】 As a concrete example, consider a case where an evacuation advisory is issued due to heavy rain in a certain area. The server receives weather information through a data collection device and quickly evaluates it using a data analysis device. It then generates an action plan, including movement to a safe evacuation site, and notifies residents via terminals. At this time, a language processing device notifies residents in the appropriate language for those who speak multiple languages. In addition, a resource mapping device distributes information to help volunteers assist with the evacuation of the elderly. Through these processes, the entire community can cooperate and evacuate safely. 【0213】 The following describes the processing flow. 【0214】 Step 1: 【0215】 The server collects data from local residents' devices and sensors. Specifically, the server receives data via an API and stores weather information, residents' health status, and current disaster information in a database. 【0216】 Step 2: 【0217】 The server analyzes data in real time using data analysis tools. For example, if it detects a sudden change in temperature or abnormal health data, it prepares to generate an alert. 【0218】 Step 3: 【0219】 The server generates an action plan based on the analyzed results. Specifically, it determines whether an evacuation order should be issued and what kind of support is needed, and then formulates a plan to address each situation. 【0220】 Step 4: 【0221】 The device receives instructions from the server and notifies the user. For example, if an evacuation advisory is included, it displays an alert on the user's smartphone and provides information on evacuation routes and shelters. 【0222】 Step 5: 【0223】 The device uses language processing to translate messages between residents who speak different languages, facilitating smooth communication. For example, a Japanese notification can be translated into English and communicated to residents in the appropriate language. 【0224】 Step 6: 【0225】 The server uses resource mapping tools to identify available personnel and resources. If necessary, it notifies volunteers and medical staff of specific tasks to encourage a rapid response. 【0226】 Step 7: 【0227】 Users act based on the information they receive to ensure their safety. For example, when heading to a designated evacuation center, residents use route guidance displayed on their devices to navigate. 【0228】 (Example 1) 【0229】 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". 【0230】 In modern society, crisis management and rapid communication within local communities are crucial challenges. In particular, delays in information and inadequate responses during disasters can exacerbate damage. Furthermore, sharing information among residents with diverse linguistic and cultural backgrounds presents significant difficulties. In this context, effective and rapid information gathering, analysis, sharing, and resource utilization are essential. 【0231】 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. 【0232】 In this invention, the server includes data acquisition means for collecting data from members of the local community, data processing means for immediately analyzing the acquired data and generating action plans, and information distribution means for notifying members of the generated action plans. This makes it possible to quickly and accurately collect and analyze information and communicate action plans to members. Furthermore, by using natural language processing means, efficient information sharing among multilingual residents becomes possible, strengthening cooperation throughout the community. 【0233】 A "member of a local community" refers to an individual or family who resides in a specific geographical area and belongs to that community. 【0234】 "Data acquisition means" refers to devices and methods for collecting various types of information from members of a local community. 【0235】 "Data processing means" refers to processes or devices that analyze acquired data and generate necessary action procedures based on that information. 【0236】 "Information distribution means" refers to a system or device for notifying members of generated action procedures and providing them with appropriate information. 【0237】 "Natural language processing means" refers to technologies for interpreting multiple languages ​​and performing translation and semantic understanding. 【0238】 "Resource identification means" refers to a system for identifying available resources and personnel and for notifying them of that information. 【0239】 This system is designed to support information gathering and problem solving within local communities. The server operates in a cloud environment and collects data from terminals and various sensor devices used by members of the community. This data includes weather information, health information, and disaster prevention information. APIs and IoT devices are used as data acquisition methods. 【0240】 The server executes data processing measures to analyze the collected data, and the software used here includes machine learning algorithms and anomaly detection algorithms for running predictive models. This analysis assesses the current situation in the region and identifies potential risks. Then, using generative AI models, appropriate action plans are automatically generated. These action plans are compiled as a list of actionable tasks and notified to members through information distribution channels. 【0241】 The terminal receives action instructions and related information transmitted from the server and displays them on the user's smartphone or on local bulletin boards. The information is provided in a format that users can immediately act upon and includes specific evacuation routes and safety measures to be followed. The terminal also uses natural language processing to enable multilingual support. This facilitates the exchange of information among residents who speak multiple languages, thereby promoting smoother communication. 【0242】 Furthermore, the server utilizes resource identification tools to identify resources and personnel within the region and sends notifications as needed. This enables the effective mobilization of volunteers and professionals, allowing for swift and appropriate support activities to address the challenges facing the community. 【0243】 As a concrete example, when a disaster is predicted, the server quickly analyzes weather data and generates action plans suggesting evacuation routes. These plans are translated into multiple languages ​​and provided to users via mobile devices. An example of a prompt to be input into the generating AI model is, "Generate the optimal action plan for the predicted disaster risk." This enables the entire community to cooperate and respond appropriately, minimizing damage. 【0244】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0245】 Step 1: 【0246】 The server collects information from terminals and sensor devices of each member of the community. Input data includes weather data, health data, and disaster prevention-related data. The server acquires this information in real time through data acquisition methods and stores it in a database. This data is then formatted and validated in preparation for subsequent analysis. 【0247】 Step 2: 【0248】 The server analyzes the collected data using data processing tools. It uses information stored in a database as input data. In the specific analysis, machine learning models and anomaly detection algorithms are employed, and as a result, evacuation advisories and health risk predictions are output. This process highlights anomalies and unique trends in the information, and action plans are generated based on this. 【0249】 Step 3: 【0250】 The server uses a generative AI model to generate action plans based on the analysis results. The analysis results from step 2 are used as input. The generated action plans include specific evacuation routes and recommended actions, and the generative AI model provides appropriate output when prompted with the message "Create the optimal action plan based on the current situation." 【0251】 Step 4: 【0252】 The terminal receives action instructions sent from the server and notifies members using an information distribution method. In this step, the generated action instructions are displayed on the user's mobile device or local bulletin board. The input is action instruction data from the server, and the output is provided as visual notifications or alerts. Users review this and take timely action according to their situation. 【0253】 Step 5: 【0254】 The terminal uses natural language processing to translate instructions and information into multiple languages. The input includes instructions received from the server, which are translated appropriately according to each member's language settings. This output enables smooth information sharing among residents who speak different languages, allowing all users to properly understand the instructions. 【0255】 Step 6: 【0256】 The server utilizes resource identification tools to identify local resources and available personnel. The input consists of collected data and analysis results. The output includes sending instructions and notifications for support activities to volunteers and professionals, enabling a rapid response across the region. 【0257】 (Application Example 1) 【0258】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0259】 In local communities, there is a need for rapid evacuation guidance during disasters and efficient provision of local information in daily life. Furthermore, promoting communication among residents and optimizing resource utilization are also important issues. However, this information is not provided in real time, and there is a lack of appropriate evacuation route guidance and multilingual support. Therefore, there is a growing need for systems that enable local residents to respond safely and appropriately. 【0260】 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. 【0261】 In this invention, the server includes information acquisition means for obtaining data from local residents, information analysis means for analyzing the acquired data with temporal realism and creating an action plan, information provision means for presenting the created action plan to local residents, language conversion means for supporting dialogue among residents, resource identification means for identifying and presenting available personnel and resources, and navigation application means for providing users with emergency evacuation routes and local information for normal times. This enables local residents to evacuate quickly during disasters and to use information efficiently in their daily lives. 【0262】 "Local residents" refers to individuals or households who live in a specific area and whose lives are affected by that area. 【0263】 "Information acquisition means" refers to devices and methods for collecting data from local residents, and includes collection processes using sensors and smart devices. 【0264】 "Information analysis means" refers to methods and technologies for processing collected data in real time, evaluating the situation, and deriving appropriate action plans. 【0265】 "Information provision means" refers to methods and devices for clearly notifying local residents of action plans and important information, and includes smartphones and digital bulletin boards. 【0266】 "Language translation means" refers to technologies and methods for translating messages in order to facilitate communication among local residents using diverse languages. 【0267】 "Resource identification methods" refer to technologies and techniques that identify human resources and material resources that can cooperate within a region, and provide information to efficiently utilize them. 【0268】 "Navigation application means" refers to technologies and devices that provide users with evacuation routes in emergencies and local information during normal times, supporting quick and appropriate action. 【0269】 This invention provides a system for effectively collecting, analyzing, and providing information within a local community. This system is implemented with a core configuration consisting of a server, terminals, and users. 【0270】 The server collects data from local residents using various data acquisition methods. This data includes various information such as location, weather conditions, and health status. The collected data is stored in a database such as AWS RDS. The server uses tools such as TensorFlow and Scikit-learn to perform real-time data analysis. Based on the analysis results, an appropriate action plan is automatically generated. 【0271】 The device, developed with React Native, functions as an information delivery tool. It displays action plans in multiple languages ​​on the user's smart device and instantly guides users to evacuation routes in emergencies. In normal times, it provides information on local events and commercial facilities, enriching the lives of local residents. 【0272】 Users access information provided by the system using smartphones and other devices. Especially in emergencies, they can respond quickly based on notifications from their devices to ensure their safety. 【0273】 As a concrete example, consider a scenario where a disaster occurs in a region. The server analyzes weather information in real time and generates an evacuation plan. The terminal notifies the user in multiple languages ​​and suggests appropriate evacuation routes. To facilitate this process, prompt statements are used as input to the generating AI model. A prompt statement such as, "Create a script that generates a rapid evacuation plan and notifies residents when a disaster occurs in the region," might be used. 【0274】 This system will enable local residents to obtain and effectively utilize necessary information in a timely manner during disasters and in their daily lives. 【0275】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0276】 Step 1: 【0277】 The server uses information acquisition methods to collect data from local residents' smart devices and sensors. The input data includes location information, weather information, and health data, which are identified, organized, and stored in AWS RDS. The output is an organized dataset. 【0278】 Step 2: 【0279】 The server uses TensorFlow as the information analysis means and analyzes the stored data in real time. Through the analysis, an algorithm for detecting outliers and emergencies is applied, and an action plan necessary for the residents is generated. The input is the organized dataset, and the output is the action plan and the result of anomaly detection. 【0280】 Step 3: 【0281】 The server utilizes the generative AI model to generate the necessary evacuation plan and action guidelines based on the prompt text. The prompt text is in the form such as "Please create a script to generate a rapid evacuation plan and notify the residents". The input is the analyzed data and the prompt text, and the output is the specific evacuation plan. 【0282】 Step 4: 【0283】 The terminal notifies the action plan to the residents' smart devices through the information providing means. The notification supports multiple languages and can be immediately conveyed by voice or push notification in case of emergency. The input is the action plan sent from the server, and the output is the notification displayed on the user's device. 【0284】 Step 5: 【0285】 The user acts quickly and accurately based on the information received from the terminal. Specific actions such as the user moving according to the evacuation route displayed on the smart device or making use of daily information are executed. The input is the notification from the terminal, and the output is the user's actual actions. 【0286】 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. 【0287】 This invention is a system that recognizes the emotional state of local residents and, based on that, provides appropriate action plans and information notifications. By combining this system with an emotion engine, it aims to add a new dimension to existing data collection, analysis, and notification processes, enabling residents to take quicker action with greater confidence. 【0288】 The server collects data from local residents' devices and sensor devices, including information for recognizing emotions such as voice data and biometric data. Using voice recognition technology and facial expression analysis, the emotion engine analyzes this data. Through this analysis, the server identifies the emotions a user is feeling in response to their situation. For example, if a resident is feeling anxious, this emotion can be used as a trigger to adjust the action plan accordingly. 【0289】 Based on the emotional states identified by the emotion engine, the server adjusts the action plan it generates. Specifically, it sends reassuring notifications to areas experiencing high levels of anxiety and, if necessary, suggests providing psychological care. When an evacuation order is issued, the server generates a notification that provides detailed instructions and support information based on the emotion analysis. 【0290】 The device receives and displays notifications tailored to each individual user, sent from the server. Depending on the user's emotions, the notification language may be softened, and information may be made visually easier to understand using illustrations and videos. For example, during an evacuation, it may provide calming messages to reduce fear and anxiety, and detailed information about the support system at the evacuation center. 【0291】 Furthermore, users can provide emotional feedback regarding questions and concerns via their devices. This information is analyzed by an emotion engine and used to improve the quality of services provided by the server. Additionally, language processing tools are adjusted based on emotions to support more effective communication among residents. 【0292】 In this way, the system of the present invention aims to improve the safety and sense of security of the entire community through flexible information provision and action plans that respond to the feelings of local residents. 【0293】 The following describes the processing flow. 【0294】 Step 1: 【0295】 The server collects data from local residents' devices and sensor equipment. This data includes voice and biosensor information and is stored in a database for analysis by the emotion engine. 【0296】 Step 2: 【0297】 The server analyzes collected voice and biometric data using an emotion engine. The emotion engine identifies the user's emotions from changes in voice tone, facial expressions, and heart rate. Examples of emotions include anxiety, anger, and relief. 【0298】 Step 3: 【0299】 The server integrates emotional information obtained from the emotion engine with existing data and performs real-time analysis. This analysis generates appropriate action plans for users with specific emotional states. 【0300】 Step 4: 【0301】 The generated action plan is fine-tuned to match the user's emotional state. For example, for anxious users, notifications and guidelines designed to promote a sense of security are incorporated. 【0302】 Step 5: 【0303】 The device receives personalized notifications sent from the server. The content of the notifications varies depending on the user's emotional state and is presented to the user at an appropriate time and with appropriate language. 【0304】 Step 6: 【0305】 The user receives a notification via the terminal and acts based on its content. Messages for reducing anxiety and detailed evacuation procedures are included, and the user refers to these to act safely. 【0306】 Step 7: 【0307】 Feedback on the emotions provided by the user is sent back to the server again and analyzed by the emotion engine. The results of this analysis are utilized for future service improvement and optimization of action plans. 【0308】 (Example 2) 【0309】 Next, Example 2 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". 【0310】 In the local community, there is a lack of means to quickly and accurately grasp the emotional states of residents and to carry out appropriate action plans and information notifications based on them. For this reason, there is a problem that it is difficult for residents to ensure safety in emergencies and daily life and to obtain a sense of security. Furthermore, the mechanism for effective communication among residents and for improving services by making use of feedback is not sufficient. 【0311】 The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following respective means. 【0312】 In this invention, the server includes an information receiving means, an emotion recognition means, a plan generation means, an information distribution means, and an opinion collection means. Thereby, it becomes possible to formulate an action plan and provide information according to the emotional states of residents, and to continuously improve services by making use of feedback. 【0313】 The "information receiving means" is a device or method for collecting data such as voice data and biometric information from people in the area. 【0314】 "Emotion recognition means" refers to a device or method for analyzing collected data and identifying residents' emotions using speech recognition technology or facial expression analysis technology. 【0315】 "Plan generation means" refers to a device or method for formulating an appropriate action plan based on the emotional state identified by the emotion recognition means. 【0316】 "Information distribution means" refers to a device or method for transmitting a formulated action plan as a notification to people's terminals and providing necessary information. 【0317】 "Means of collecting opinions" refers to devices or methods for collecting feedback from residents and using it to improve the system. 【0318】 This invention is a system that recognizes the emotional state of people in a region in real time and provides action plans and information notifications based on that recognition. This system operates with a server at its core, working in conjunction with terminals and various sensors. 【0319】 The server receives information collected from local residents. Data collected from terminals and sensor devices includes voice data and biometric information. Voice data is acquired using the terminal's microphone, and biometric information is acquired from wearable devices such as smartwatches and smart bands. This data is aggregated on the server and analyzed using voice recognition software and facial expression analysis algorithms. Specifically, "Google Speech-to-Text API" and "Microsoft Azure Speech Service" can be used for voice recognition, and "OpenCV" can be used for facial expression analysis. 【0320】 The emotion recognition engine identifies people's emotional states based on these analysis results. For example, it can detect stress and anxiety from changes in voice tone and biometric information. Based on this emotional state, the server uses a generative AI model to formulate an action plan. Specifically, it creates messages to provide reassurance and provides information on evacuation routes and psychological care when needed. 【0321】 The device visually displays notifications sent from the server to users. These notifications include soft language, illustrations, and videos tailored to the user's emotional state, designed for intuitive understanding. For example, during an evacuation advisory, a calming message is displayed to alleviate fear, along with detailed information about evacuation shelters. 【0322】 Furthermore, users can send feedback to the server through their devices. This feedback is used to improve the system's performance. For example, prompts such as, "Please tell us how you are feeling right now. This information will help us improve the service," can be displayed. An example of a prompt might be, "Analyze how local residents are feeling about the disaster and generate notifications to encourage evacuation accordingly. These notifications should include reassuring messages and detailed information about evacuation shelters." 【0323】 In this way, the system of the present invention improves safety and security in local communities. 【0324】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0325】 Step 1: 【0326】 The server collects voice data and biometric information from terminals and sensor devices. Inputs include voice data obtained from the terminal's microphone and biometric information such as heart rate and skin temperature collected from wearable devices. This data is aggregated on the server and prepared for emotion analysis. 【0327】 Step 2: 【0328】 The server performs emotion recognition based on the collected data. The input consists of voice data and biometric information collected in step 1. The server analyzes this data using voice recognition software and facial expression analysis algorithms. For example, it analyzes voice tone to determine stress levels or observes changes in heart rate to infer feelings of anxiety. The output identifies the emotional state of the residents (e.g., reassured, stressed, anxious). 【0329】 Step 3: 【0330】 The server generates an action plan based on the identified emotional state. The input is the emotional state data from step 2. The server utilizes a generative AI model to analyze what information and actions residents need and formulate an appropriate action plan. For example, if it determines that a person is feeling anxious, it will create a message to provide reassurance. The output will be an action plan and notification messages. 【0331】 Step 4: 【0332】 The server adjusts the information notification based on the generated action plan and sends it to the terminal. The input is the notification message generated in step 3. The server adjusts the notification content to suit the residents' sentiments and makes it visually easy to understand. For example, it may include illustrations or videos to make the information easier to receive. The output is the adjusted notification sent to the residents' terminals. 【0333】 Step 5: 【0334】 The terminal displays notifications received from the server to the user. The input is the notification message sent in step 4. The terminal displays the notification in the user interface, using, for example, gentle colors and animations to alleviate anxiety. The output is the visual notification information received by the user. 【0335】 Step 6: 【0336】 Users provide feedback and send it to the server. Input consists of the user's emotions and responses to notifications. Users submit comments and feedback using the feedback function configured on their device. The server receives this feedback data and uses it to plan future actions and improve the service. Output is data for more refined sentiment analysis and service improvement. 【0337】 (Application Example 2) 【0338】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0339】 In modern urban environments, accurately understanding the emotional state of local residents and responding quickly and appropriately is essential. However, existing systems fail to adequately provide emotion-based action plans and information dissemination, hindering the creation of safe and secure cities. In particular, when residents' anxiety and fear escalate, delays in appropriate responses can lead to social unrest. To address these challenges, a system is needed that recognizes residents' emotional states in real time and provides corresponding response measures. 【0340】 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. 【0341】 In this invention, the server includes information gathering means for collecting information from local groups, information analysis means for analyzing the collected information in real time and creating an action plan, and emotion recognition means for recognizing emotional states and providing a sense of security. This enables flexible information provision and action planning based on the emotions of residents. 【0342】 "Information gathering methods" refer to methods for obtaining diverse forms of data from local groups. 【0343】 "Information analysis means" refers to a method for generating action plans by performing real-time analysis based on collected data. 【0344】 "Information transmission methods" refer to methods for effectively communicating created action plans and related information to a group. 【0345】 "Language processing means" refers to methods related to language processing that support communication between groups and effectively convey information. 【0346】 "Resource allocation means" refers to methods for optimally allocating available personnel and resources and notifying the group accordingly. 【0347】 "Emotion recognition methods" are techniques for identifying residents' emotional states and providing them with a sense of security. 【0348】 The system for realizing this invention mainly consists of a server, terminals, and users. The server acquires diverse data from local groups using information gathering means. Specifically, it utilizes hardware that collects voice and facial expression data through smartphones and sensor devices. This makes it possible to obtain detailed information about the emotional state of local residents. 【0349】 Next, the server processes and analyzes the collected data in real time using information analysis tools. This process utilizes cloud services and speech recognition technologies (e.g., Google Cloud Speech-to-Text and OpenCV). The analyzed data is then used to evaluate the emotional state of residents using emotion recognition tools, and an action plan is generated based on this evaluation. A key feature of this action plan is that it enables flexible information suggestions tailored to individual emotions. 【0350】 The generated action plan is communicated to the user via a terminal using an information transmission method. The display on the terminal incorporates emotionally-based message adjustments, and visual information is used to promote a sense of security among residents. For example, a smartphone application might be used to display text with soft language and illustrations in gentle colors. 【0351】 Furthermore, user feedback is sent to the server via the user's device. This information is analyzed by language processing tools to improve future services. Additionally, residents can feel a sense of security and support when providing feedback about their emotions. 【0352】 As a concrete example, if residents experience stress during an event in a certain area, the server will quickly recognize this emotion and generate a prompt message suggesting the event organizers to introduce a relaxation space. The system might propose a prompt message such as, "Based on the emotional data collected from event participants in this area, please evaluate the emotional state of the residents and consider countermeasures to provide them with a sense of security." 【0353】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0354】 Step 1: 【0355】 The server uses information gathering tools to acquire voice and facial expression data from local communities via smartphones and sensor devices. Inputs include real-time voice and image data transmitted from various devices. By collecting this data, the server can prepare a dataset that reflects the environment and emotional state of local residents. 【0356】 Step 2: 【0357】 The server processes the acquired audio and facial expression data in real time using information analysis tools. It utilizes Google Cloud Speech-to-Text to convert audio data into text data. It also uses OpenCV to analyze facial expression images and extract emotional parameters. The input consists of audio and image data, and the output is data indicating emotional states. This process generates foundational data for identifying the emotional states of residents. 【0358】 Step 3: 【0359】 The server evaluates the analyzed data using emotion recognition tools and identifies the emotional state of the residents. Using a generative AI model, it analyzes the emotional data from multiple perspectives and generates an action plan that reflects the current situation in the region. The input is emotional parameters, and the output is an action plan corresponding to those emotions. This step allows us to understand what kind of response the residents of the region need. 【0360】 Step 4: 【0361】 The server notifies the group of the generated action plan via an information transmission mechanism. The terminal receives the notification and displays a message on the screen in a soft tone that matches the user's emotions. For example, in addition to text messages, illustrations with calming colors are used. The input is the action plan, and the output is in the form of a screen display on the terminal. This notification gives the user a sense of security. 【0362】 Step 5: 【0363】 Users send feedback to the server via their devices. The server analyzes this information using language processing tools to improve future services. The input is user feedback data, and the output is an action plan for service improvement. Specifically, residents provide feedback after events, which is then used to plan future events. 【0364】 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. 【0365】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0366】 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. 【0367】 [Third Embodiment] 【0368】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0369】 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. 【0370】 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). 【0371】 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. 【0372】 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. 【0373】 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). 【0374】 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. 【0375】 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. 【0376】 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. 【0377】 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. 【0378】 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. 【0379】 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". 【0380】 This invention is a system designed to enable local residents to respond quickly and appropriately to various challenges during disasters and in their daily lives. This system promotes community mutual assistance by analyzing information collected from residents, generating and sharing necessary action plans, and providing support to the community. 【0381】 The server receives information from local residents' devices and sensor devices using data collection methods. This information includes weather data, health data, disaster prevention-related information, etc., and is stored in a database on the server. 【0382】 The server analyzes the data accumulated by data analysis tools in real time. During this process, it uses predictive models and anomaly detection algorithms to quickly grasp the situation and automatically generate action plans as needed. These generated plans are then prioritized based on their importance and urgency. 【0383】 The terminal receives action plans and information sent from the server and displays them on the user's smartphone or on local bulletin boards. This information sharing method allows residents to take appropriate action. For example, when an evacuation order is issued, the terminal immediately sends a notification to the user. 【0384】 The device also supports communication among residents through language processing capabilities. Natural language processing technology translates messages into multiple languages, including foreign languages, facilitating smooth information exchange. 【0385】 Furthermore, the server uses resource mapping to identify available personnel and resources based on the collected information. This allows for rapid notification to local residents as needed, enabling the deployment of effective support activities. 【0386】 As a concrete example, consider a case where an evacuation advisory is issued due to heavy rain in a certain area. The server receives weather information through a data collection device and quickly evaluates it using a data analysis device. It then generates an action plan, including movement to a safe evacuation site, and notifies residents via terminals. At this time, a language processing device notifies residents in the appropriate language for those who speak multiple languages. In addition, a resource mapping device distributes information to help volunteers assist with the evacuation of the elderly. Through these processes, the entire community can cooperate and evacuate safely. 【0387】 The following describes the processing flow. 【0388】 Step 1: 【0389】 The server collects data from local residents' devices and sensors. Specifically, the server receives data via an API and stores weather information, residents' health status, and current disaster information in a database. 【0390】 Step 2: 【0391】 The server analyzes data in real time using data analysis tools. For example, if it detects a sudden change in temperature or abnormal health data, it prepares to generate an alert. 【0392】 Step 3: 【0393】 The server generates an action plan based on the analyzed results. Specifically, it determines whether an evacuation order should be issued and what kind of support is needed, and then formulates a plan to address each situation. 【0394】 Step 4: 【0395】 The device receives instructions from the server and notifies the user. For example, if an evacuation advisory is included, it displays an alert on the user's smartphone and provides information on evacuation routes and shelters. 【0396】 Step 5: 【0397】 The device uses language processing to translate messages between residents who speak different languages, facilitating smooth communication. For example, a Japanese notification can be translated into English and communicated to residents in the appropriate language. 【0398】 Step 6: 【0399】 The server uses resource mapping tools to identify available personnel and resources. If necessary, it notifies volunteers and medical staff of specific tasks to encourage a rapid response. 【0400】 Step 7: 【0401】 Users act based on the information they receive to ensure their safety. For example, when heading to a designated evacuation center, residents use route guidance displayed on their devices to navigate. 【0402】 (Example 1) 【0403】 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." 【0404】 In modern society, crisis management and rapid communication within local communities are crucial challenges. In particular, delays in information and inadequate responses during disasters can exacerbate damage. Furthermore, sharing information among residents with diverse linguistic and cultural backgrounds presents significant difficulties. In this context, effective and rapid information gathering, analysis, sharing, and resource utilization are essential. 【0405】 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. 【0406】 In this invention, the server includes data acquisition means for collecting data from members of the local community, data processing means for immediately analyzing the acquired data and generating action plans, and information distribution means for notifying members of the generated action plans. This makes it possible to quickly and accurately collect and analyze information and communicate action plans to members. Furthermore, by using natural language processing means, efficient information sharing among multilingual residents becomes possible, strengthening cooperation throughout the community. 【0407】 A "member of a local community" refers to an individual or family who resides in a specific geographical area and belongs to that community. 【0408】 "Data acquisition means" refers to devices and methods for collecting various types of information from members of a local community. 【0409】 "Data processing means" refers to processes or devices that analyze acquired data and generate necessary action procedures based on that information. 【0410】 "Information distribution means" refers to a system or device for notifying members of generated action procedures and providing them with appropriate information. 【0411】 "Natural language processing means" refers to technologies for interpreting multiple languages ​​and performing translation and semantic understanding. 【0412】 "Resource identification means" refers to a system for identifying available resources and personnel and for notifying them of that information. 【0413】 This system is designed to support information gathering and problem solving within local communities. The server operates in a cloud environment and collects data from terminals and various sensor devices used by members of the community. This data includes weather information, health information, and disaster prevention information. APIs and IoT devices are used as data acquisition methods. 【0414】 The server executes data processing measures to analyze the collected data, and the software used here includes machine learning algorithms and anomaly detection algorithms for running predictive models. This analysis assesses the current situation in the region and identifies potential risks. Then, using generative AI models, appropriate action plans are automatically generated. These action plans are compiled as a list of actionable tasks and notified to members through information distribution channels. 【0415】 The terminal receives action instructions and related information transmitted from the server and displays them on the user's smartphone or on local bulletin boards. The information is provided in a format that users can immediately act upon and includes specific evacuation routes and safety measures to be followed. The terminal also uses natural language processing to enable multilingual support. This facilitates the exchange of information among residents who speak multiple languages, thereby promoting smoother communication. 【0416】 Furthermore, the server utilizes resource identification tools to identify resources and personnel within the region and sends notifications as needed. This enables the effective mobilization of volunteers and professionals, allowing for swift and appropriate support activities to address the challenges facing the community. 【0417】 As a concrete example, when a disaster is predicted, the server quickly analyzes weather data and generates action plans suggesting evacuation routes. These plans are translated into multiple languages ​​and provided to users via mobile devices. An example of a prompt to be input into the generating AI model is, "Generate the optimal action plan for the predicted disaster risk." This enables the entire community to cooperate and respond appropriately, minimizing damage. 【0418】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0419】 Step 1: 【0420】 The server collects information from terminals and sensor devices of each member of the community. Input data includes weather data, health data, and disaster prevention-related data. The server acquires this information in real time through data acquisition methods and stores it in a database. This data is then formatted and validated in preparation for subsequent analysis. 【0421】 Step 2: 【0422】 The server analyzes the collected data using data processing tools. It uses information stored in a database as input data. In the specific analysis, machine learning models and anomaly detection algorithms are employed, and as a result, evacuation advisories and health risk predictions are output. This process highlights anomalies and unique trends in the information, and action plans are generated based on this. 【0423】 Step 3: 【0424】 The server uses a generative AI model to generate action plans based on the analysis results. The analysis results from step 2 are used as input. The generated action plans include specific evacuation routes and recommended actions, and the generative AI model provides appropriate output when prompted with the message "Create the optimal action plan based on the current situation." 【0425】 Step 4: 【0426】 The terminal receives action instructions sent from the server and notifies members using an information distribution method. In this step, the generated action instructions are displayed on the user's mobile device or local bulletin board. The input is action instruction data from the server, and the output is provided as visual notifications or alerts. Users review this and take timely action according to their situation. 【0427】 Step 5: 【0428】 The terminal uses natural language processing to translate instructions and information into multiple languages. The input includes instructions received from the server, which are translated appropriately according to each member's language settings. This output enables smooth information sharing among residents who speak different languages, allowing all users to properly understand the instructions. 【0429】 Step 6: 【0430】 The server utilizes resource identification tools to identify local resources and available personnel. The input consists of collected data and analysis results. The output includes sending instructions and notifications for support activities to volunteers and professionals, enabling a rapid response across the region. 【0431】 (Application Example 1) 【0432】 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." 【0433】 In local communities, there is a need for rapid evacuation guidance during disasters and efficient provision of local information in daily life. Furthermore, promoting communication among residents and optimizing resource utilization are also important issues. However, this information is not provided in real time, and there is a lack of appropriate evacuation route guidance and multilingual support. Therefore, there is a growing need for systems that enable local residents to respond safely and appropriately. 【0434】 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. 【0435】 In this invention, the server includes information acquisition means for obtaining data from local residents, information analysis means for analyzing the acquired data with temporal realism and creating an action plan, information provision means for presenting the created action plan to local residents, language conversion means for supporting dialogue among residents, resource identification means for identifying and presenting available personnel and resources, and navigation application means for providing users with emergency evacuation routes and local information for normal times. This enables local residents to evacuate quickly during disasters and to use information efficiently in their daily lives. 【0436】 "Local residents" refers to individuals or households who live in a specific area and whose lives are affected by that area. 【0437】 "Information acquisition means" refers to devices and methods for collecting data from local residents, and includes collection processes using sensors and smart devices. 【0438】 "Information analysis means" refers to methods and technologies for processing collected data in real time, evaluating the situation, and deriving appropriate action plans. 【0439】 "Information provision means" refers to methods and devices for clearly notifying local residents of action plans and important information, and includes smartphones and digital bulletin boards. 【0440】 "Language translation means" refers to technologies and methods for translating messages in order to facilitate communication among local residents using diverse languages. 【0441】 "Resource identification methods" refer to technologies and techniques that identify human resources and material resources that can cooperate within a region, and provide information to efficiently utilize them. 【0442】 "Navigation application means" refers to technologies and devices that provide users with evacuation routes in emergencies and local information during normal times, supporting quick and appropriate action. 【0443】 This invention provides a system for effectively collecting, analyzing, and providing information within a local community. This system is implemented with a core configuration consisting of a server, terminals, and users. 【0444】 The server collects data from local residents using various data acquisition methods. This data includes various information such as location, weather conditions, and health status. The collected data is stored in a database such as AWS RDS. The server uses tools such as TensorFlow and Scikit-learn to perform real-time data analysis. Based on the analysis results, an appropriate action plan is automatically generated. 【0445】 The device, developed with React Native, functions as an information delivery tool. It displays action plans in multiple languages ​​on the user's smart device and instantly guides users to evacuation routes in emergencies. In normal times, it provides information on local events and commercial facilities, enriching the lives of local residents. 【0446】 Users access information provided by the system using smartphones and other devices. Especially in emergencies, they can respond quickly based on notifications from their devices to ensure their safety. 【0447】 As a concrete example, consider a scenario where a disaster occurs in a region. The server analyzes weather information in real time and generates an evacuation plan. The terminal notifies the user in multiple languages ​​and suggests appropriate evacuation routes. To facilitate this process, prompt statements are used as input to the generating AI model. A prompt statement such as, "Create a script that generates a rapid evacuation plan and notifies residents when a disaster occurs in the region," might be used. 【0448】 This system will enable local residents to obtain and effectively utilize necessary information in a timely manner during disasters and in their daily lives. 【0449】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0450】 Step 1: 【0451】 The server uses information acquisition methods to collect data from local residents' smart devices and sensors. The input data includes location information, weather information, and health data, which are identified, organized, and stored in AWS RDS. The output is an organized dataset. 【0452】 Step 2: 【0453】 The server uses TensorFlow as its data analysis tool to analyze stored data in real time. Through this analysis, algorithms are applied to detect anomalies and emergencies, and action plans necessary for residents are generated. The input is a well-organized dataset, and the output consists of action plans and anomaly detection results. 【0454】 Step 3: 【0455】 The server utilizes a generation AI model to generate necessary evacuation plans and action guidelines based on prompt messages. Prompt messages are in the format of "Please create a script to generate a rapid evacuation plan and notify residents." Input consists of analyzed data and prompt messages, while output is a specific evacuation plan. 【0456】 Step 4: 【0457】 The terminal notifies residents of action plans via information delivery methods on their smart devices. The notifications are multilingual and, in emergencies, can be immediately conveyed via voice or push notifications. The input is the action plan sent from the server, and the output is the notification displayed on the user's device. 【0458】 Step 5: 【0459】 Users take swift and accurate action based on information received from their devices. This includes specific actions such as following evacuation routes displayed on their smart devices or utilizing everyday information. The input is notifications from the device, and the output is the user's actual actions. 【0460】 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. 【0461】 This invention is a system that recognizes the emotional state of local residents and, based on that, provides appropriate action plans and information notifications. By combining this system with an emotion engine, it aims to add a new dimension to existing data collection, analysis, and notification processes, enabling residents to take quicker action with greater confidence. 【0462】 The server collects data from local residents' devices and sensor devices, including information for recognizing emotions such as voice data and biometric data. Using voice recognition technology and facial expression analysis, the emotion engine analyzes this data. Through this analysis, the server identifies the emotions a user is feeling in response to their situation. For example, if a resident is feeling anxious, this emotion can be used as a trigger to adjust the action plan accordingly. 【0463】 Based on the emotional states identified by the emotion engine, the server adjusts the action plan it generates. Specifically, it sends reassuring notifications to areas experiencing high levels of anxiety and, if necessary, suggests providing psychological care. When an evacuation order is issued, the server generates a notification that provides detailed instructions and support information based on the emotion analysis. 【0464】 The device receives and displays notifications tailored to each individual user, sent from the server. Depending on the user's emotions, the notification language may be softened, and information may be made visually easier to understand using illustrations and videos. For example, during an evacuation, it may provide calming messages to reduce fear and anxiety, and detailed information about the support system at the evacuation center. 【0465】 Furthermore, users can provide emotional feedback regarding questions and concerns via their devices. This information is analyzed by an emotion engine and used to improve the quality of services provided by the server. Additionally, language processing tools are adjusted based on emotions to support more effective communication among residents. 【0466】 In this way, the system of the present invention aims to improve the safety and sense of security of the entire community through flexible information provision and action plans that respond to the feelings of local residents. 【0467】 The following describes the processing flow. 【0468】 Step 1: 【0469】 The server collects data from local residents' devices and sensor equipment. This data includes voice and biosensor information and is stored in a database for analysis by the emotion engine. 【0470】 Step 2: 【0471】 The server analyzes collected voice and biometric data using an emotion engine. The emotion engine identifies the user's emotions from changes in voice tone, facial expressions, and heart rate. Examples of emotions include anxiety, anger, and relief. 【0472】 Step 3: 【0473】 The server integrates emotional information obtained from the emotion engine with existing data and performs real-time analysis. This analysis generates appropriate action plans for users with specific emotional states. 【0474】 Step 4: 【0475】 The generated action plan is fine-tuned to match the user's emotional state. For example, for anxious users, notifications and guidelines designed to promote a sense of security are incorporated. 【0476】 Step 5: 【0477】 The device receives personalized notifications sent from the server. The content of the notifications varies depending on the user's emotional state and is presented to the user at an appropriate time and with appropriate language. 【0478】 Step 6: 【0479】 Users receive notifications via their devices and act accordingly. These notifications include messages to alleviate anxiety and detailed evacuation procedures, which users refer to to ensure their safety. 【0480】 Step 7: 【0481】 The emotional feedback provided by users is sent back to the server and analyzed by the emotion engine. The results of this analysis are used to improve future services and optimize action plans. 【0482】 (Example 2) 【0483】 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." 【0484】 In local communities, there is a lack of means to quickly and accurately grasp the emotional state of residents and to develop appropriate action plans and provide information based on that understanding. This creates a problem where residents have difficulty ensuring their safety and sense of security during emergencies and in their daily lives. Furthermore, there are insufficient mechanisms for effective communication among residents and for using feedback to improve services. 【0485】 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. 【0486】 In this invention, the server includes an information receiving means, an emotion recognition means, a plan generation means, an information distribution means, and an opinion collection means. This enables the formulation of action plans and information provision in accordance with the emotional state of residents, and continuous improvement of services using feedback. 【0487】 "Information receiving means" refers to a device or method for collecting data such as voice data and biometric information from people in a local area. 【0488】 "Emotion recognition means" refers to a device or method for analyzing collected data and identifying residents' emotions using speech recognition technology or facial expression analysis technology. 【0489】 "Plan generation means" refers to a device or method for formulating an appropriate action plan based on the emotional state identified by the emotion recognition means. 【0490】 "Information distribution means" refers to a device or method for transmitting a formulated action plan as a notification to people's terminals and providing necessary information. 【0491】 "Means of collecting opinions" refers to devices or methods for collecting feedback from residents and using it to improve the system. 【0492】 This invention is a system that recognizes the emotional state of people in a region in real time and provides action plans and information notifications based on that recognition. This system operates with a server at its core, working in conjunction with terminals and various sensors. 【0493】 The server receives information collected from local residents. Data collected from terminals and sensor devices includes voice data and biometric information. Voice data is acquired using the terminal's microphone, and biometric information is acquired from wearable devices such as smartwatches and smart bands. This data is aggregated on the server and analyzed using voice recognition software and facial expression analysis algorithms. Specifically, "Google Speech-to-Text API" and "Microsoft Azure Speech Service" can be used for voice recognition, and "OpenCV" can be used for facial expression analysis. 【0494】 The emotion recognition engine identifies people's emotional states based on these analysis results. For example, it can detect stress and anxiety from changes in voice tone and biometric information. Based on this emotional state, the server uses a generative AI model to formulate an action plan. Specifically, it creates messages to provide reassurance and provides information on evacuation routes and psychological care when needed. 【0495】 The device visually displays notifications sent from the server to users. These notifications include soft language, illustrations, and videos tailored to the user's emotional state, designed for intuitive understanding. For example, during an evacuation advisory, a calming message is displayed to alleviate fear, along with detailed information about evacuation shelters. 【0496】 Furthermore, users can send feedback to the server through their devices. This feedback is used to improve the system's performance. For example, prompts such as, "Please tell us how you are feeling right now. This information will help us improve the service," can be displayed. An example of a prompt might be, "Analyze how local residents are feeling about the disaster and generate notifications to encourage evacuation accordingly. These notifications should include reassuring messages and detailed information about evacuation shelters." 【0497】 In this way, the system of the present invention improves safety and security in local communities. 【0498】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0499】 Step 1: 【0500】 The server collects voice data and biometric information from terminals and sensor devices. Inputs include voice data obtained from the terminal's microphone and biometric information such as heart rate and skin temperature collected from wearable devices. This data is aggregated on the server and prepared for emotion analysis. 【0501】 Step 2: 【0502】 The server performs emotion recognition based on the collected data. The input consists of voice data and biometric information collected in step 1. The server analyzes this data using voice recognition software and facial expression analysis algorithms. For example, it analyzes voice tone to determine stress levels or observes changes in heart rate to infer feelings of anxiety. The output identifies the emotional state of the residents (e.g., reassured, stressed, anxious). 【0503】 Step 3: 【0504】 The server generates an action plan based on the identified emotional state. The input is the emotional state data from step 2. The server utilizes a generative AI model to analyze what information and actions residents need and formulate an appropriate action plan. For example, if it determines that a person is feeling anxious, it will create a message to provide reassurance. The output will be an action plan and notification messages. 【0505】 Step 4: 【0506】 The server adjusts the information notification based on the generated action plan and sends it to the terminal. The input is the notification message generated in step 3. The server adjusts the notification content to suit the residents' sentiments and makes it visually easy to understand. For example, it may include illustrations or videos to make the information easier to receive. The output is the adjusted notification sent to the residents' terminals. 【0507】 Step 5: 【0508】 The terminal displays notifications received from the server to the user. The input is the notification message sent in step 4. The terminal displays the notification in the user interface, using, for example, gentle colors and animations to alleviate anxiety. The output is the visual notification information received by the user. 【0509】 Step 6: 【0510】 Users provide feedback and send it to the server. Input consists of the user's emotions and responses to notifications. Users submit comments and feedback using the feedback function configured on their device. The server receives this feedback data and uses it to plan future actions and improve the service. Output is data for more refined sentiment analysis and service improvement. 【0511】 (Application Example 2) 【0512】 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." 【0513】 In modern urban environments, accurately understanding the emotional state of local residents and responding quickly and appropriately is essential. However, existing systems fail to adequately provide emotion-based action plans and information dissemination, hindering the creation of safe and secure cities. In particular, when residents' anxiety and fear escalate, delays in appropriate responses can lead to social unrest. To address these challenges, a system is needed that recognizes residents' emotional states in real time and provides corresponding response measures. 【0514】 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. 【0515】 In this invention, the server includes information gathering means for collecting information from local groups, information analysis means for analyzing the collected information in real time and creating an action plan, and emotion recognition means for recognizing emotional states and providing a sense of security. This enables flexible information provision and action planning based on the emotions of residents. 【0516】 "Information gathering methods" refer to methods for obtaining diverse forms of data from local groups. 【0517】 "Information analysis means" refers to a method for generating action plans by performing real-time analysis based on collected data. 【0518】 "Information transmission methods" refer to methods for effectively communicating created action plans and related information to a group. 【0519】 "Language processing means" refers to methods related to language processing that support communication between groups and effectively convey information. 【0520】 "Resource allocation means" refers to methods for optimally allocating available personnel and resources and notifying the group accordingly. 【0521】 "Emotion recognition methods" are techniques for identifying residents' emotional states and providing them with a sense of security. 【0522】 The system for realizing this invention mainly consists of a server, terminals, and users. The server acquires diverse data from local groups using information gathering means. Specifically, it utilizes hardware that collects voice and facial expression data through smartphones and sensor devices. This makes it possible to obtain detailed information about the emotional state of local residents. 【0523】 Next, the server processes and analyzes the collected data in real time using information analysis tools. This process utilizes cloud services and speech recognition technologies (e.g., Google Cloud Speech-to-Text and OpenCV). The analyzed data is then used to evaluate the emotional state of residents using emotion recognition tools, and an action plan is generated based on this evaluation. A key feature of this action plan is that it enables flexible information suggestions tailored to individual emotions. 【0524】 The generated action plan is communicated to the user via a terminal using an information transmission method. The display on the terminal incorporates emotionally-based message adjustments, and visual information is used to promote a sense of security among residents. For example, a smartphone application might be used to display text with soft language and illustrations in gentle colors. 【0525】 Furthermore, user feedback is sent to the server via the user's device. This information is analyzed by language processing tools to improve future services. Additionally, residents can feel a sense of security and support when providing feedback about their emotions. 【0526】 As a concrete example, if residents experience stress during an event in a certain area, the server will quickly recognize this emotion and generate a prompt message suggesting the event organizers to introduce a relaxation space. The system might propose a prompt message such as, "Based on the emotional data collected from event participants in this area, please evaluate the emotional state of the residents and consider countermeasures to provide them with a sense of security." 【0527】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0528】 Step 1: 【0529】 The server uses information gathering tools to acquire voice and facial expression data from local communities via smartphones and sensor devices. Inputs include real-time voice and image data transmitted from various devices. By collecting this data, the server can prepare a dataset that reflects the environment and emotional state of local residents. 【0530】 Step 2: 【0531】 The server processes the acquired audio and facial expression data in real time using information analysis tools. It utilizes Google Cloud Speech-to-Text to convert audio data into text data. It also uses OpenCV to analyze facial expression images and extract emotional parameters. The input consists of audio and image data, and the output is data indicating emotional states. This process generates foundational data for identifying the emotional states of residents. 【0532】 Step 3: 【0533】 The server evaluates the analyzed data using emotion recognition tools and identifies the emotional state of the residents. Using a generative AI model, it analyzes the emotional data from multiple perspectives and generates an action plan that reflects the current situation in the region. The input is emotional parameters, and the output is an action plan corresponding to those emotions. This step allows us to understand what kind of response the residents of the region need. 【0534】 Step 4: 【0535】 The server notifies the group of the generated action plan via an information transmission mechanism. The terminal receives the notification and displays a message on the screen in a soft tone that matches the user's emotions. For example, in addition to text messages, illustrations with calming colors are used. The input is the action plan, and the output is in the form of a screen display on the terminal. This notification gives the user a sense of security. 【0536】 Step 5: 【0537】 Users send feedback to the server via their devices. The server analyzes this information using language processing tools to improve future services. The input is user feedback data, and the output is an action plan for service improvement. Specifically, residents provide feedback after events, which is then used to plan future events. 【0538】 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. 【0539】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0540】 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. 【0541】 [Fourth Embodiment] 【0542】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0543】 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. 【0544】 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). 【0545】 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. 【0546】 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. 【0547】 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). 【0548】 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. 【0549】 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. 【0550】 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. 【0551】 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. 【0552】 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. 【0553】 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. 【0554】 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". 【0555】 This invention is a system designed to enable local residents to respond quickly and appropriately to various challenges during disasters and in their daily lives. This system promotes community mutual assistance by analyzing information collected from residents, generating and sharing necessary action plans, and providing support to the community. 【0556】 The server receives information from local residents' devices and sensor devices using data collection methods. This information includes weather data, health data, disaster prevention-related information, etc., and is stored in a database on the server. 【0557】 The server analyzes the data accumulated by data analysis tools in real time. During this process, it uses predictive models and anomaly detection algorithms to quickly grasp the situation and automatically generate action plans as needed. These generated plans are then prioritized based on their importance and urgency. 【0558】 The terminal receives action plans and information sent from the server and displays them on the user's smartphone or on local bulletin boards. This information sharing method allows residents to take appropriate action. For example, when an evacuation order is issued, the terminal immediately sends a notification to the user. 【0559】 The device also supports communication among residents through language processing capabilities. Natural language processing technology translates messages into multiple languages, including foreign languages, facilitating smooth information exchange. 【0560】 Furthermore, the server uses resource mapping to identify available personnel and resources based on the collected information. This allows for rapid notification to local residents as needed, enabling the deployment of effective support activities. 【0561】 As a concrete example, consider a case where an evacuation advisory is issued due to heavy rain in a certain area. The server receives weather information through a data collection device and quickly evaluates it using a data analysis device. It then generates an action plan, including movement to a safe evacuation site, and notifies residents via terminals. At this time, a language processing device notifies residents in the appropriate language for those who speak multiple languages. In addition, a resource mapping device distributes information to help volunteers assist with the evacuation of the elderly. Through these processes, the entire community can cooperate and evacuate safely. 【0562】 The following describes the processing flow. 【0563】 Step 1: 【0564】 The server collects data from local residents' devices and sensors. Specifically, the server receives data via an API and stores weather information, residents' health status, and current disaster information in a database. 【0565】 Step 2: 【0566】 The server analyzes data in real time using data analysis tools. For example, if it detects a sudden change in temperature or abnormal health data, it prepares to generate an alert. 【0567】 Step 3: 【0568】 The server generates an action plan based on the analyzed results. Specifically, it determines whether an evacuation order should be issued and what kind of support is needed, and then formulates a plan to address each situation. 【0569】 Step 4: 【0570】 The device receives instructions from the server and notifies the user. For example, if an evacuation advisory is included, it displays an alert on the user's smartphone and provides information on evacuation routes and shelters. 【0571】 Step 5: 【0572】 The device uses language processing to translate messages between residents who speak different languages, facilitating smooth communication. For example, a Japanese notification can be translated into English and communicated to residents in the appropriate language. 【0573】 Step 6: 【0574】 The server uses resource mapping tools to identify available personnel and resources. If necessary, it notifies volunteers and medical staff of specific tasks to encourage a rapid response. 【0575】 Step 7: 【0576】 Users act based on the information they receive to ensure their safety. For example, when heading to a designated evacuation center, residents use route guidance displayed on their devices to navigate. 【0577】 (Example 1) 【0578】 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". 【0579】 In modern society, crisis management and rapid communication within local communities are crucial challenges. In particular, delays in information and inadequate responses during disasters can exacerbate damage. Furthermore, sharing information among residents with diverse linguistic and cultural backgrounds presents significant difficulties. In this context, effective and rapid information gathering, analysis, sharing, and resource utilization are essential. 【0580】 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. 【0581】 In this invention, the server includes data acquisition means for collecting data from members of the local community, data processing means for immediately analyzing the acquired data and generating action plans, and information distribution means for notifying members of the generated action plans. This makes it possible to quickly and accurately collect and analyze information and communicate action plans to members. Furthermore, by using natural language processing means, efficient information sharing among multilingual residents becomes possible, strengthening cooperation throughout the community. 【0582】 A "member of a local community" refers to an individual or family who resides in a specific geographical area and belongs to that community. 【0583】 "Data acquisition means" refers to devices and methods for collecting various types of information from members of a local community. 【0584】 "Data processing means" refers to processes or devices that analyze acquired data and generate necessary action procedures based on that information. 【0585】 "Information distribution means" refers to a system or device for notifying members of generated action procedures and providing them with appropriate information. 【0586】 "Natural language processing means" refers to technologies for interpreting multiple languages ​​and performing translation and semantic understanding. 【0587】 "Resource identification means" refers to a system for identifying available resources and personnel and for notifying them of that information. 【0588】 This system is designed to support information gathering and problem solving within local communities. The server operates in a cloud environment and collects data from terminals and various sensor devices used by members of the community. This data includes weather information, health information, and disaster prevention information. APIs and IoT devices are used as data acquisition methods. 【0589】 The server executes data processing measures to analyze the collected data, and the software used here includes machine learning algorithms and anomaly detection algorithms for running predictive models. This analysis assesses the current situation in the region and identifies potential risks. Then, using generative AI models, appropriate action plans are automatically generated. These action plans are compiled as a list of actionable tasks and notified to members through information distribution channels. 【0590】 The terminal receives action instructions and related information transmitted from the server and displays them on the user's smartphone or on local bulletin boards. The information is provided in a format that users can immediately act upon and includes specific evacuation routes and safety measures to be followed. The terminal also uses natural language processing to enable multilingual support. This facilitates the exchange of information among residents who speak multiple languages, thereby promoting smoother communication. 【0591】 Furthermore, the server utilizes resource identification tools to identify resources and personnel within the region and sends notifications as needed. This enables the effective mobilization of volunteers and professionals, allowing for swift and appropriate support activities to address the challenges facing the community. 【0592】 As a concrete example, when a disaster is predicted, the server quickly analyzes weather data and generates action plans suggesting evacuation routes. These plans are translated into multiple languages ​​and provided to users via mobile devices. An example of a prompt to be input into the generating AI model is, "Generate the optimal action plan for the predicted disaster risk." This enables the entire community to cooperate and respond appropriately, minimizing damage. 【0593】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0594】 Step 1: 【0595】 The server collects information from terminals and sensor devices of each member of the community. Input data includes weather data, health data, and disaster prevention-related data. The server acquires this information in real time through data acquisition methods and stores it in a database. This data is then formatted and validated in preparation for subsequent analysis. 【0596】 Step 2: 【0597】 The server analyzes the collected data using data processing tools. It uses information stored in a database as input data. In the specific analysis, machine learning models and anomaly detection algorithms are employed, and as a result, evacuation advisories and health risk predictions are output. This process highlights anomalies and unique trends in the information, and action plans are generated based on this. 【0598】 Step 3: 【0599】 The server uses a generative AI model to generate action plans based on the analysis results. The analysis results from step 2 are used as input. The generated action plans include specific evacuation routes and recommended actions, and the generative AI model provides appropriate output when prompted with the message "Create the optimal action plan based on the current situation." 【0600】 Step 4: 【0601】 The terminal receives action instructions sent from the server and notifies members using an information distribution method. In this step, the generated action instructions are displayed on the user's mobile device or local bulletin board. The input is action instruction data from the server, and the output is provided as visual notifications or alerts. Users review this and take timely action according to their situation. 【0602】 Step 5: 【0603】 The terminal uses natural language processing to translate instructions and information into multiple languages. The input includes instructions received from the server, which are translated appropriately according to each member's language settings. This output enables smooth information sharing among residents who speak different languages, allowing all users to properly understand the instructions. 【0604】 Step 6: 【0605】 The server utilizes resource identification tools to identify local resources and available personnel. The input consists of collected data and analysis results. The output includes sending instructions and notifications for support activities to volunteers and professionals, enabling a rapid response across the region. 【0606】 (Application Example 1) 【0607】 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". 【0608】 In local communities, there is a need for rapid evacuation guidance during disasters and efficient provision of local information in daily life. Furthermore, promoting communication among residents and optimizing resource utilization are also important issues. However, this information is not provided in real time, and there is a lack of appropriate evacuation route guidance and multilingual support. Therefore, there is a growing need for systems that enable local residents to respond safely and appropriately. 【0609】 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. 【0610】 In this invention, the server includes information acquisition means for obtaining data from local residents, information analysis means for analyzing the acquired data with temporal realism and creating an action plan, information provision means for presenting the created action plan to local residents, language conversion means for supporting dialogue among residents, resource identification means for identifying and presenting available personnel and resources, and navigation application means for providing users with emergency evacuation routes and local information for normal times. This enables local residents to evacuate quickly during disasters and to use information efficiently in their daily lives. 【0611】 "Local residents" refers to individuals or households who live in a specific area and whose lives are affected by that area. 【0612】 "Information acquisition means" refers to devices and methods for collecting data from local residents, and includes collection processes using sensors and smart devices. 【0613】 "Information analysis means" refers to methods and technologies for processing collected data in real time, evaluating the situation, and deriving appropriate action plans. 【0614】 "Information provision means" refers to methods and devices for clearly notifying local residents of action plans and important information, and includes smartphones and digital bulletin boards. 【0615】 "Language translation means" refers to technologies and methods for translating messages in order to facilitate communication among local residents using diverse languages. 【0616】 "Resource identification methods" refer to technologies and techniques that identify human resources and material resources that can cooperate within a region, and provide information to efficiently utilize them. 【0617】 "Navigation application means" refers to technologies and devices that provide users with evacuation routes in emergencies and local information during normal times, supporting quick and appropriate action. 【0618】 This invention provides a system for effectively collecting, analyzing, and providing information within a local community. This system is implemented with a core configuration consisting of a server, terminals, and users. 【0619】 The server collects data from local residents using various data acquisition methods. This data includes various information such as location, weather conditions, and health status. The collected data is stored in a database such as AWS RDS. The server uses tools such as TensorFlow and Scikit-learn to perform real-time data analysis. Based on the analysis results, an appropriate action plan is automatically generated. 【0620】 The device, developed with React Native, functions as an information delivery tool. It displays action plans in multiple languages ​​on the user's smart device and instantly guides users to evacuation routes in emergencies. In normal times, it provides information on local events and commercial facilities, enriching the lives of local residents. 【0621】 Users access information provided by the system using smartphones and other devices. Especially in emergencies, they can respond quickly based on notifications from their devices to ensure their safety. 【0622】 As a concrete example, consider a scenario where a disaster occurs in a region. The server analyzes weather information in real time and generates an evacuation plan. The terminal notifies the user in multiple languages ​​and suggests appropriate evacuation routes. To facilitate this process, prompt statements are used as input to the generating AI model. A prompt statement such as, "Create a script that generates a rapid evacuation plan and notifies residents when a disaster occurs in the region," might be used. 【0623】 This system will enable local residents to obtain and effectively utilize necessary information in a timely manner during disasters and in their daily lives. 【0624】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0625】 Step 1: 【0626】 The server uses information acquisition methods to collect data from local residents' smart devices and sensors. The input data includes location information, weather information, and health data, which are identified, organized, and stored in AWS RDS. The output is an organized dataset. 【0627】 Step 2: 【0628】 The server uses TensorFlow as its data analysis tool to analyze stored data in real time. Through this analysis, algorithms are applied to detect anomalies and emergencies, and action plans necessary for residents are generated. The input is a well-organized dataset, and the output consists of action plans and anomaly detection results. 【0629】 Step 3: 【0630】 The server utilizes a generation AI model to generate necessary evacuation plans and action guidelines based on prompt messages. Prompt messages are in the format of "Please create a script to generate a rapid evacuation plan and notify residents." Input consists of analyzed data and prompt messages, while output is a specific evacuation plan. 【0631】 Step 4: 【0632】 The terminal notifies residents of action plans via information delivery methods on their smart devices. The notifications are multilingual and, in emergencies, can be immediately conveyed via voice or push notifications. The input is the action plan sent from the server, and the output is the notification displayed on the user's device. 【0633】 Step 5: 【0634】 Users take swift and accurate action based on information received from their devices. This includes specific actions such as following evacuation routes displayed on their smart devices or utilizing everyday information. The input is notifications from the device, and the output is the user's actual actions. 【0635】 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. 【0636】 This invention is a system that recognizes the emotional state of local residents and, based on that, provides appropriate action plans and information notifications. By combining this system with an emotion engine, it aims to add a new dimension to existing data collection, analysis, and notification processes, enabling residents to take quicker action with greater confidence. 【0637】 The server collects data from local residents' devices and sensor devices, including information for recognizing emotions such as voice data and biometric data. Using voice recognition technology and facial expression analysis, the emotion engine analyzes this data. Through this analysis, the server identifies the emotions a user is feeling in response to their situation. For example, if a resident is feeling anxious, this emotion can be used as a trigger to adjust the action plan accordingly. 【0638】 Based on the emotional states identified by the emotion engine, the server adjusts the action plan it generates. Specifically, it sends reassuring notifications to areas experiencing high levels of anxiety and, if necessary, suggests providing psychological care. When an evacuation order is issued, the server generates a notification that provides detailed instructions and support information based on the emotion analysis. 【0639】 The device receives and displays notifications tailored to each individual user, sent from the server. Depending on the user's emotions, the notification language may be softened, and information may be made visually easier to understand using illustrations and videos. For example, during an evacuation, it may provide calming messages to reduce fear and anxiety, and detailed information about the support system at the evacuation center. 【0640】 Furthermore, users can provide emotional feedback regarding questions and concerns via their devices. This information is analyzed by an emotion engine and used to improve the quality of services provided by the server. Additionally, language processing tools are adjusted based on emotions to support more effective communication among residents. 【0641】 In this way, the system of the present invention aims to improve the safety and sense of security of the entire community through flexible information provision and action plans that respond to the feelings of local residents. 【0642】 The following describes the processing flow. 【0643】 Step 1: 【0644】 The server collects data from local residents' devices and sensor equipment. This data includes voice and biosensor information and is stored in a database for analysis by the emotion engine. 【0645】 Step 2: 【0646】 The server analyzes collected voice and biometric data using an emotion engine. The emotion engine identifies the user's emotions from changes in voice tone, facial expressions, and heart rate. Examples of emotions include anxiety, anger, and relief. 【0647】 Step 3: 【0648】 The server integrates emotional information obtained from the emotion engine with existing data and performs real-time analysis. This analysis generates appropriate action plans for users with specific emotional states. 【0649】 Step 4: 【0650】 The generated action plan is fine-tuned to match the user's emotional state. For example, for anxious users, notifications and guidelines designed to promote a sense of security are incorporated. 【0651】 Step 5: 【0652】 The device receives personalized notifications sent from the server. The content of the notifications varies depending on the user's emotional state and is presented to the user at an appropriate time and with appropriate language. 【0653】 Step 6: 【0654】 Users receive notifications via their devices and act accordingly. These notifications include messages to alleviate anxiety and detailed evacuation procedures, which users refer to to ensure their safety. 【0655】 Step 7: 【0656】 The emotional feedback provided by users is sent back to the server and analyzed by the emotion engine. The results of this analysis are used to improve future services and optimize action plans. 【0657】 (Example 2) 【0658】 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". 【0659】 In local communities, there is a lack of means to quickly and accurately grasp the emotional state of residents and to develop appropriate action plans and provide information based on that understanding. This creates a problem where residents have difficulty ensuring their safety and sense of security during emergencies and in their daily lives. Furthermore, there are insufficient mechanisms for effective communication among residents and for using feedback to improve services. 【0660】 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. 【0661】 In this invention, the server includes an information receiving means, an emotion recognition means, a plan generation means, an information distribution means, and an opinion collection means. This enables the formulation of action plans and information provision in accordance with the emotional state of residents, and continuous improvement of services using feedback. 【0662】 "Information receiving means" refers to a device or method for collecting data such as voice data and biometric information from people in a local area. 【0663】 "Emotion recognition means" refers to a device or method for analyzing collected data and identifying residents' emotions using speech recognition technology or facial expression analysis technology. 【0664】 "Plan generation means" refers to a device or method for formulating an appropriate action plan based on the emotional state identified by the emotion recognition means. 【0665】 "Information distribution means" refers to a device or method for transmitting a formulated action plan as a notification to people's terminals and providing necessary information. 【0666】 "Means of collecting opinions" refers to devices or methods for collecting feedback from residents and using it to improve the system. 【0667】 This invention is a system that recognizes the emotional state of people in a region in real time and provides action plans and information notifications based on that recognition. This system operates with a server at its core, working in conjunction with terminals and various sensors. 【0668】 The server receives information collected from local residents. Data collected from terminals and sensor devices includes voice data and biometric information. Voice data is acquired using the terminal's microphone, and biometric information is acquired from wearable devices such as smartwatches and smart bands. This data is aggregated on the server and analyzed using voice recognition software and facial expression analysis algorithms. Specifically, "Google Speech-to-Text API" and "Microsoft Azure Speech Service" can be used for voice recognition, and "OpenCV" can be used for facial expression analysis. 【0669】 The emotion recognition engine identifies people's emotional states based on these analysis results. For example, it can detect stress and anxiety from changes in voice tone and biometric information. Based on this emotional state, the server uses a generative AI model to formulate an action plan. Specifically, it creates messages to provide reassurance and provides information on evacuation routes and psychological care when needed. 【0670】 The device visually displays notifications sent from the server to users. These notifications include soft language, illustrations, and videos tailored to the user's emotional state, designed for intuitive understanding. For example, during an evacuation advisory, a calming message is displayed to alleviate fear, along with detailed information about evacuation shelters. 【0671】 Furthermore, users can send feedback to the server through their devices. This feedback is used to improve the system's performance. For example, prompts such as, "Please tell us how you are feeling right now. This information will help us improve the service," can be displayed. An example of a prompt might be, "Analyze how local residents are feeling about the disaster and generate notifications to encourage evacuation accordingly. These notifications should include reassuring messages and detailed information about evacuation shelters." 【0672】 In this way, the system of the present invention improves safety and security in local communities. 【0673】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0674】 Step 1: 【0675】 The server collects voice data and biometric information from terminals and sensor devices. Inputs include voice data obtained from the terminal's microphone and biometric information such as heart rate and skin temperature collected from wearable devices. This data is aggregated on the server and prepared for emotion analysis. 【0676】 Step 2: 【0677】 The server performs emotion recognition based on the collected data. The input consists of voice data and biometric information collected in step 1. The server analyzes this data using voice recognition software and facial expression analysis algorithms. For example, it analyzes voice tone to determine stress levels or observes changes in heart rate to infer feelings of anxiety. The output identifies the emotional state of the residents (e.g., reassured, stressed, anxious). 【0678】 Step 3: 【0679】 The server generates an action plan based on the identified emotional state. The input is the emotional state data from step 2. The server utilizes a generative AI model to analyze what information and actions residents need and formulate an appropriate action plan. For example, if it determines that a person is feeling anxious, it will create a message to provide reassurance. The output will be an action plan and notification messages. 【0680】 Step 4: 【0681】 The server adjusts the information notification based on the generated action plan and sends it to the terminal. The input is the notification message generated in step 3. The server adjusts the notification content to suit the residents' sentiments and makes it visually easy to understand. For example, it may include illustrations or videos to make the information easier to receive. The output is the adjusted notification sent to the residents' terminals. 【0682】 Step 5: 【0683】 The terminal displays notifications received from the server to the user. The input is the notification message sent in step 4. The terminal displays the notification in the user interface, using, for example, gentle colors and animations to alleviate anxiety. The output is the visual notification information received by the user. 【0684】 Step 6: 【0685】 Users provide feedback and send it to the server. Input consists of the user's emotions and responses to notifications. Users submit comments and feedback using the feedback function configured on their device. The server receives this feedback data and uses it to plan future actions and improve the service. Output is data for more refined sentiment analysis and service improvement. 【0686】 (Application Example 2) 【0687】 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". 【0688】 In modern urban environments, accurately understanding the emotional state of local residents and responding quickly and appropriately is essential. However, existing systems fail to adequately provide emotion-based action plans and information dissemination, hindering the creation of safe and secure cities. In particular, when residents' anxiety and fear escalate, delays in appropriate responses can lead to social unrest. To address these challenges, a system is needed that recognizes residents' emotional states in real time and provides corresponding response measures. 【0689】 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. 【0690】 In this invention, the server includes information gathering means for collecting information from local groups, information analysis means for analyzing the collected information in real time and creating an action plan, and emotion recognition means for recognizing emotional states and providing a sense of security. This enables flexible information provision and action planning based on the emotions of residents. 【0691】 "Information gathering methods" refer to methods for obtaining diverse forms of data from local groups. 【0692】 "Information analysis means" refers to a method for generating action plans by performing real-time analysis based on collected data. 【0693】 "Information transmission methods" refer to methods for effectively communicating created action plans and related information to a group. 【0694】 "Language processing means" refers to methods related to language processing that support communication between groups and effectively convey information. 【0695】 "Resource allocation means" refers to methods for optimally allocating available personnel and resources and notifying the group accordingly. 【0696】 "Emotion recognition methods" are techniques for identifying residents' emotional states and providing them with a sense of security. 【0697】 The system for realizing this invention mainly consists of a server, terminals, and users. The server acquires diverse data from local groups using information gathering means. Specifically, it utilizes hardware that collects voice and facial expression data through smartphones and sensor devices. This makes it possible to obtain detailed information about the emotional state of local residents. 【0698】 Next, the server processes and analyzes the collected data in real time using information analysis tools. This process utilizes cloud services and speech recognition technologies (e.g., Google Cloud Speech-to-Text and OpenCV). The analyzed data is then used to evaluate the emotional state of residents using emotion recognition tools, and an action plan is generated based on this evaluation. A key feature of this action plan is that it enables flexible information suggestions tailored to individual emotions. 【0699】 The generated action plan is communicated to the user via a terminal using an information transmission method. The display on the terminal incorporates emotionally-based message adjustments, and visual information is used to promote a sense of security among residents. For example, a smartphone application might be used to display text with soft language and illustrations in gentle colors. 【0700】 Furthermore, user feedback is sent to the server via the user's device. This information is analyzed by language processing tools to improve future services. Additionally, residents can feel a sense of security and support when providing feedback about their emotions. 【0701】 As a concrete example, if residents experience stress during an event in a certain area, the server will quickly recognize this emotion and generate a prompt message suggesting the event organizers to introduce a relaxation space. The system might propose a prompt message such as, "Based on the emotional data collected from event participants in this area, please evaluate the emotional state of the residents and consider countermeasures to provide them with a sense of security." 【0702】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0703】 Step 1: 【0704】 The server uses information gathering tools to acquire voice and facial expression data from local communities via smartphones and sensor devices. Inputs include real-time voice and image data transmitted from various devices. By collecting this data, the server can prepare a dataset that reflects the environment and emotional state of local residents. 【0705】 Step 2: 【0706】 The server processes the acquired audio and facial expression data in real time using information analysis tools. It utilizes Google Cloud Speech-to-Text to convert audio data into text data. It also uses OpenCV to analyze facial expression images and extract emotional parameters. The input consists of audio and image data, and the output is data indicating emotional states. This process generates foundational data for identifying the emotional states of residents. 【0707】 Step 3: 【0708】 The server evaluates the analyzed data using emotion recognition tools and identifies the emotional state of the residents. Using a generative AI model, it analyzes the emotional data from multiple perspectives and generates an action plan that reflects the current situation in the region. The input is emotional parameters, and the output is an action plan corresponding to those emotions. This step allows us to understand what kind of response the residents of the region need. 【0709】 Step 4: 【0710】 The server notifies the group of the generated action plan via an information transmission mechanism. The terminal receives the notification and displays a message on the screen in a soft tone that matches the user's emotions. For example, in addition to text messages, illustrations with calming colors are used. The input is the action plan, and the output is in the form of a screen display on the terminal. This notification gives the user a sense of security. 【0711】 Step 5: 【0712】 Users send feedback to the server via their devices. The server analyzes this information using language processing tools to improve future services. The input is user feedback data, and the output is an action plan for service improvement. Specifically, residents provide feedback after events, which is then used to plan future events. 【0713】 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. 【0714】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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. 【0715】 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. 【0716】 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. 【0717】 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. 【0718】 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. 【0719】 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. 【0720】 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. 【0721】 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." 【0722】 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. 【0723】 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. 【0724】 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. 【0725】 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. 【0726】 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. 【0727】 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. 【0728】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0729】 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. 【0730】 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. 【0731】 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. 【0732】 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. 【0733】 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. 【0734】 The following is further disclosed regarding the embodiments described above. 【0735】 (Claim 1) 【0736】 Data collection methods for gathering information from local residents, 【0737】 A data analysis tool for analyzing collected data in real time and generating an action plan, 【0738】 A means of sharing information to notify residents of the generated action plan, 【0739】 Language processing tools to support communication among residents, 【0740】 A resource mapping method for mapping and notifying about available personnel and resources, 【0741】 A system that includes this. 【0742】 (Claim 2) 【0743】 The system according to claim 1, wherein the data analysis means performs a process to detect anomalies and trends based on the data and to list tasks that require action. 【0744】 (Claim 3) 【0745】 The system according to claim 1, wherein the information sharing means sends notifications to residents' terminals and provides specific actions such as evacuation orders and support. 【0746】 "Example 1" 【0747】 (Claim 1) 【0748】 Data acquisition methods for collecting data from members of the local community, 【0749】 A data processing means for immediately analyzing acquired data and generating action procedures, 【0750】 Information distribution means for notifying members of the generated action procedures, 【0751】 A natural language processing tool to support information exchange among members, 【0752】 Resource identification means for identifying and notifying available resources and personnel, 【0753】 A system that includes this. 【0754】 (Claim 2) 【0755】 The system according to claim 1, wherein the data processing means performs a process to identify exceptional values ​​or trends based on the data and organize the tasks that require action. 【0756】 (Claim 3) 【0757】 The system according to claim 1, wherein the information distribution means transmits a notification to the information terminal of a member and provides specific tasks for evacuation orders or support. 【0758】 "Application Example 1" 【0759】 (Claim 1) 【0760】 Information acquisition methods for obtaining data from local residents, 【0761】 An information analysis tool for analyzing acquired data with time-sensitive accuracy and generating action plans, 【0762】 A means of providing information to local residents to present the created action plan, 【0763】 Language conversion tools to support dialogue among residents, 【0764】 Resource identification means for identifying and presenting personnel and resources that can cooperate, 【0765】 A navigation application means for providing users with emergency evacuation routes and local information during normal times, 【0766】 A system that includes this. 【0767】 (Claim 2) 【0768】 The system according to claim 1, wherein the information analysis means performs a process to identify abnormal values ​​or trends based on data and list the issues that require attention. 【0769】 (Claim 3) 【0770】 The system according to claim 1, wherein the information provision means transmits selected instructions to the terminals of local residents and presents evacuation orders and specific action plans for support. 【0771】 "Example 2 of combining an emotion engine" 【0772】 (Claim 1) 【0773】 A means of receiving information to collect information from local people, 【0774】 A means of emotion recognition for analyzing collected information and identifying emotional states, 【0775】 A plan generation means for creating an action plan based on emotional state, 【0776】 Means of distributing information to provide people with the action plan that has been formulated, 【0777】 A means of collecting opinions so that people can provide feedback and contribute to improving the service, 【0778】 A system that includes this. 【0779】 (Claim 2) 【0780】 The system according to claim 1, wherein the emotion recognition means performs a process of identifying an emotion based on data and adjusting an action plan based on that emotion. 【0781】 (Claim 3) 【0782】 The system according to claim 1, wherein the information distribution means sends emotion-responsive notifications to people's terminals and provides specific support. 【0783】 "Application example 2 of combining emotional engines" 【0784】 (Claim 1) 【0785】 Information gathering methods for collecting information from local groups, 【0786】 Information analysis means for analyzing collected information in real time and creating action plans, 【0787】 A means of communicating the created action plan to the group, 【0788】 Language processing means to support communication between groups, 【0789】 Resource allocation means for assigning and notifying people and resources that can cooperate, 【0790】 A means of recognizing emotional states and providing a sense of security, 【0791】 A system that includes this. 【0792】 (Claim 2) 【0793】 The system according to claim 1, wherein the information analysis means detects outliers and trends based on the information and performs a process to list the tasks that require action. 【0794】 (Claim 3) 【0795】 The system according to claim 1, wherein the information transmission means transmits a notification to a group of devices and provides specific actions such as evacuation orders or support. [Explanation of symbols] 【0796】 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] Data collection methods for gathering information from local residents, A data analysis tool for analyzing collected data in real time and generating an action plan, A means of sharing information to notify residents of the generated action plan, Language processing tools to support communication among residents, A resource mapping method for mapping and notifying about available personnel and resources, A system that includes this. [Claim 2] The system according to claim 1, wherein the data analysis means performs a process to detect anomalies and trends based on the data and to list tasks that require action. [Claim 3] The system according to claim 1, wherein the information sharing means sends notifications to residents' terminals and provides specific actions such as evacuation orders and support.

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