system

Abstract

We provide the system. [Solution] A human interface means for collecting user opinions, Information processing tools for analyzing collected data and formulating urban plans, A display means that visualizes the analysis results and enables simulation in a virtual environment, An open API means that enables collaboration with multiple developers, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern urban planning, in order to meet the needs of an advanced society and aim for sustainable development, it is necessary to appropriately process and utilize a large amount of diverse data. However, it has been difficult to effectively collect the opinions of residents and reflect them in urban planning in real time using conventional methods. Also, the interface for expanding the system in cooperation with engineers in different fields has been complex. By solving such problems, it is required to realize an efficient and flexible urban planning.

Means for Solving the Problems

[0005] This invention provides a system equipped with a human interface means for collecting user opinions, an information processing means for analyzing the collected data and formulating urban plans, a display means for visualizing the analysis results and enabling simulation in a virtual environment, and an open API means for collaboration with multiple developers. This system solves conventional problems by enabling real-time opinion collection and processing, effective simulation using virtual or augmented reality, and enhanced scalability through external collaboration.

[0006] A "user" is an individual or group that accesses the system and provides feedback.

[0007] "Human interface means" refers to devices or software that allow users to input opinions and information into a system.

[0008] "Data" refers to various pieces of information related to urban planning recorded as numerical or string data, including demographic trends and user opinions.

[0009] "Information processing means" refers to devices and programs that analyze collected data and generate information necessary for urban planning.

[0010] "Analysis results" refer to the results based on data analyzed by information processing tools, and are used in the formulation of urban plans.

[0011] "Visualization" refers to converting analysis results into a visually understandable form such as diagrams, graphs, or 3D models.

[0012] A "virtual environment" is a digital environment that resembles the real world and is created using computer technology.

[0013] "Simulation" refers to a trial-and-error process conducted in a virtual environment, and is used to aid in planning.

[0014] The "display means" refers to a device or program for presenting to the user the analysis results or visualizations of simulations.

[0015] The "open API means" refers to an interface that enables external developers to develop new functions and tools in cooperation with the system.

[0016] A "developer" refers to a technician or engineer who performs system expansion or new function development.

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0020] 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 CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0021] 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.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] 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."

[0025] [First Embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

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

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention is a system for collecting residents' opinions and incorporating them into urban planning in order to support the sustainable development of local communities. The system operates primarily around three elements: a server, terminals, and users, and aims to improve the efficiency of urban planning through effective cooperation between them.

[0039] The server uses a data collection module to gather diverse data from local governments and social media in real time and store it in a dedicated database. This data includes multifaceted information such as local demographics and the latest opinions of residents.

[0040] Furthermore, the server uses advanced information processing tools to analyze the collected data. Using sophisticated machine learning algorithms, it predicts population growth and decline, as well as economic trends. The results of this analysis are visualized on a dashboard and provided to terminal users via their devices.

[0041] The terminal functions as an interface between residents and the local government, providing a user interface for residents to access. Through this interface, users can submit their opinions and proposed plans. These opinions are sent to the server and incorporated into the analysis.

[0042] The terminal also features display methods that utilize virtual environments and augmented reality technology. This allows users to visually confirm simulations based on their proposals and intuitively understand the impact of their plans.

[0043] Furthermore, the server provides an open API, allowing external developers to add new functionality to the system. The open API facilitates smooth data exchange between the server and external programs. This creates an environment where residents, local businesses, and universities can collaborate to develop solutions that address region-specific challenges.

[0044] As a concrete example, in areas with an aging population, a server identifies the increasing trend of elderly people through data analysis. Using terminals, feedback is received from residents, and simulations are conducted to improve the design of public facilities based on that feedback. As a result, efficient and livable urban design becomes possible.

[0045] This invention aims to realize flexible and sustainable urban planning by incorporating a community-based, resident-participatory approach into the system.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The server collects demographic and environmental data from open data sources provided by local governments and stores it in a database. It also obtains residents' opinions and trend data in real time through social media APIs.

[0049] Step 2:

[0050] The server cleanses the collected data, removing unnecessary data and imputing missing values. The data is then formatted to a format suitable for analysis.

[0051] Step 3:

[0052] The server uses machine learning algorithms to predict demographic and economic trends and generate analysis results. This allows for the evaluation of future changes and their incorporation into planning.

[0053] Step 4:

[0054] The terminal provides a user interface for resident participation. Through this interface, users can input suggestions and opinions regarding urban planning.

[0055] Step 5:

[0056] The server receives opinion data from residents and incorporates it as part of the data analysis. The analysis results, which take residents' opinions into account, are displayed on a dashboard.

[0057] Step 6:

[0058] The device runs simulations using VR or AR technology, allowing users to experience proposed urban planning changes in a virtual space. Through this experience, users can participate in optimizing the plan.

[0059] Step 7:

[0060] The server provides data access to external developers through open APIs, supporting the development of additional features and new tools. This facilitates the development of region-specific solutions.

[0061] (Example 1)

[0062] 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."

[0063] Modern urban planning not only struggles to adequately reflect the opinions of local communities, but also requires rapid responses to predicted demographic changes and technological advancements. However, traditional methods struggle with rapid and accurate data collection and analysis, and the environment for diverse stakeholders to collaborate and expand functionality is not adequately developed. New tools are needed to improve this situation and realize sustainable urban planning.

[0064] 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.

[0065] In this invention, the server includes data processing means for collecting and analyzing data, a display device for visualizing the analyzed information and enabling simulations in a virtual space, and a public API means for enabling collaboration with multiple engineers. This makes it possible to collect opinions from local residents in real time, predict demographic changes, and conduct planning simulations in a virtual space, while developing sustainable urban plans optimized for the region through collaboration with diverse stakeholders.

[0066] A "human interface means" is a means by which users input opinions into a system and obtain information.

[0067] "Data processing means" refers to means for analyzing collected data and extracting relevant information.

[0068] A "display device" is a means of visualizing analyzed information in the form of graphics or videos and presenting it in a way that is easy for users to understand.

[0069] A "public API means" is a means of providing an interface that allows external engineers to add new functions to a system or utilize existing data.

[0070] A "machine learning algorithm" is an algorithm that learns patterns and trends from large amounts of data to predict future population trends and economic conditions.

[0071] "External platform integration means" refers to means for exchanging data with other systems and applications and extending their functionality.

[0072] This invention is an urban planning system designed to support the sustainable development of local communities. The system primarily consists of three elements: a server, terminals, and users.

[0073] The server utilizes a data collection module to collect data in real time from local governments and online platforms. The data is automatically recorded in a dedicated database via an API over the internet. The collected information includes residents' opinions, demographic trends, and economic indicators. The server then analyzes the data using machine learning algorithms written in programming languages ​​such as Python and R. This makes it possible to predict future population trends and socioeconomic trends. The analysis results are displayed on a dashboard using visualization tools and sent to the user's device.

[0074] The terminal functions as an interface with residents and local government officials. Users can directly input their opinions and suggestions using the interface provided on the terminal. This information is sent to a server and used for analysis. The terminal also features display functions using virtual reality (VR) and augmented reality (AR) technologies. This allows for the visual presentation of simulations based on suggestions, and users can see the impact in real time. For example, by using a VR headset or an AR application on a smartphone, users can experience future urban design.

[0075] Users can submit opinions to the system via their devices and receive feedback. This enables community-participatory urban planning. Users can also view the provided simulations, develop new proposals, and input them back into the system. This process allows for flexible urban planning based on the diverse needs of the community.

[0076] As a concrete example, in areas with an aging population, a server performs data analysis to identify an increasing trend in residents aged 60 and over. Opinions on improving access to public facilities are collected from residents via terminals, and simulations based on these opinions are provided on the terminals. This allows residents to virtually try out the improvement proposals they have made. An example of a prompt for the generated AI model is, "Please create a proposal for sustainable urban planning based on local demographics and residents' opinions. Please include ideas for design improvements to public facilities in areas with an aging population."

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The server collects data from local governments and online platforms via APIs. The data received as input includes residents' opinions, local demographics, and economic activity information. Storing this data in a dedicated database enables real-time information updates. Specifically, a program operates that periodically collects publicly available data from local governments and feeds from social media via a network connection.

[0080] Step 2:

[0081] The server inputs the collected data into a machine learning algorithm for analysis. This process classifies and aggregates the information to predict demographic trends and identify trends in economic activity. The output includes predictions of future trends and regional opinion tendencies. Specifically, statistical analysis libraries such as Python are used to train and infer the model.

[0082] Step 3:

[0083] The server visualizes the analysis results in a dashboard format and sends them to the terminal. The input is the analyzed data, and the output is visualized graphs and charts. Specifically, it uses data visualization tools to graphically transform the data and delivers it to the terminal via a web interface.

[0084] Step 4:

[0085] The terminal displays visualized data in a user interface. Users view this, intuitively understand the information, and input their own opinions. In this step, resident feedback is added as user input, which is then incorporated into the next data collection cycle. Specifically, the terminal accepts user input via a touchscreen or keyboard and sends it to a server.

[0086] Step 5:

[0087] The device uses virtual and augmented reality to provide a simulation of urban planning based on user proposals. The input is the user's proposal, and the output is a simulated urban environment. Specifically, the device generates a virtual model using a 3D graphics engine and performs the simulation via a VR / AR device.

[0088] Step 6:

[0089] The server allows external engineers to add functionality to the system through an open API. The input is a new external program, and the output is a system with extensions that integrate that program. Specifically, it processes API requests, stores the results in a database, and applies them to the entire system.

[0090] This series of steps enables the collection of community opinions in a readily accessible format in real time, and allows for sustainable urban planning based on data analysis.

[0091] (Application Example 1)

[0092] 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."

[0093] In urban planning aimed at the sustainable development of local communities, it is crucial to effectively collect and reflect the diverse opinions of residents. However, traditional systems have suffered from problems such as insufficient visibility of residents' proposals and difficulties in smooth communication between planners and residents. Furthermore, the lack of means to promote residents' intuitive understanding of new urban planning proposals has hindered the effective implementation of plans.

[0094] 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.

[0095] In this invention, the server includes a human interface means for collecting user opinions, an information processing means for analyzing the collected data and formulating urban plans, a display means for visualizing the analysis results and enabling simulation of user proposals in a virtual environment, and a means for providing visual feedback on the plan using augmented reality technology. This makes it possible to intuitively understand residents' proposals and to communicate smoothly with planners.

[0096] "Human interface means for collecting opinions" refers to communication technologies and devices for obtaining feedback and suggestions from users in real time.

[0097] "Information processing tools for analyzing data and formulating urban plans" refer to algorithms and computer programs that automatically generate plans for urban development and problem solving based on collected data.

[0098] "A display means that visualizes analysis results and enables user proposals to be simulated in a virtual environment" refers to a technological device that graphically represents the results of data analysis and enables users to test their proposed plans in a virtual environment.

[0099] "Means of providing visual feedback on plans using augmented reality technology" refers to devices or software that utilize augmented reality technology to visually present a proposed plan to the user in a way that overlays it onto the real world, thereby facilitating understanding.

[0100] "Development support tools" refer to technical foundations and platforms that enable multiple developers to collaborate in adding or improving new features to a system.

[0101] The system for implementing this invention has the following configuration in order to contribute to the sustainable development of the local community.

[0102] The server leverages a cloud computing platform with advanced data analysis capabilities to collect user feedback and perform real-time data processing for use in urban planning. To this end, it utilizes machine learning tools from Google Cloud Platform to collect diverse data from local governments and social media, storing it in Firebase. Machine learning algorithms are applied to the analysis, predicting regional demographics and economic trends. The analysis results are visualized on a dashboard and provided to users.

[0103] The terminal serves as an interface for residents to access the system and features a cross-platform application developed with React Native. Users can easily submit opinions and suggestions using this application. These opinions are sent to the server and used for analysis.

[0104] Furthermore, the Unity engine and AR Foundation will be used as simulation tools utilizing augmented reality technology. This will allow users to visualize their proposed urban plans in a virtual environment and intuitively verify them. For example, a user can submit a proposal for a new park and then view its completed image using AR.

[0105] As a concrete example, we can propose a design for a multi-purpose plaza where elderly people can gather in an aging community. An example of a prompt to input into the generating AI model would be, "I have submitted a design for a multi-purpose plaza for the elderly. I would like to check the completed image using AR."

[0106] In this way, the system can directly reflect residents' opinions in urban planning and promote communication between residents and planners.

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] Users input opinions and suggestions via a terminal. The input data is sent to the server through a human interface. Here, the input is the user's opinions and suggestions, and the output is data packets based on them that are sent to the server.

[0110] Step 2:

[0111] The server saves the received opinions and suggestions to GOOGLE FI® rebase. Here, the input is the data packet sent in step 1, and the output is the status of completion of saving to the database. The saved data is then subjected to subsequent analysis processing.

[0112] Step 3:

[0113] The server analyzes the stored data using machine learning tools on Google Cloud Platform. Here, the input consists of user opinions and city data stored in a database, and the output obtained from the analysis is predictions of demographic and economic trends. This analysis is performed by combining data processing and machine learning algorithms.

[0114] Step 4:

[0115] The server visualizes the analysis results on a dashboard and sends them to the terminal. The input is the analysis results, and the output is the visualized data. Through this data, the user can check the predicted results of the proposed urban plan.

[0116] Step 5:

[0117] Through an application on their device, users utilize the Unity engine and AR Foundation to run virtual simulations based on their proposals. The input consists of the user's proposal and visualization data, while the output is visual feedback in an AR environment. This process allows users to intuitively understand the feasibility and impact of their proposals.

[0118] 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.

[0119] This invention provides an urban planning system that considers not only the opinions of residents but also their emotional states. This enables a more sophisticated form of resident-participatory planning. The system consists of three elements: a server, terminals, and users, and their roles are interconnected.

[0120] The server first has the function of collecting data from local governments and social media, and this data is stored in a database. It also has an information processing system equipped with an emotion engine, which allows it to analyze the emotional state of users. The server uses this emotion data to supplement the information on the background in which residents' opinions were submitted and to perform a more detailed analysis.

[0121] The terminal provides a means for residents to input opinions and suggestions through a user interface. In addition, the terminal works in conjunction with an emotion engine to collect emotional data expressed by users during their interaction with the interface. This emotional data is immediately transmitted to a server and recorded in a database.

[0122] The server analyzes emotional data during the information processing process and generates urban planning proposals that take this into account. The analysis results are displayed on a dashboard and provided in a visually easy-to-understand format for users. By analyzing emotional data, it is also possible to pre-evaluate the level of public acceptance of the plan.

[0123] Furthermore, the device is equipped with display methods that utilize virtual reality and augmented reality. Users can experience the proposed plan in a virtual environment, and the emotional changes they experience are analyzed again by an emotion engine and sent to the server as immediate feedback. This allows for real-time adjustments to the urban plan.

[0124] As a concrete example of considering emotions, in a new park design plan, the server analyzes emotional data such as residents' expectations and concerns about the plan, along with their opinions. If a user feels enjoyment or reassurance during a simulation experience using a terminal, the direction of the plan can be fine-tuned accordingly.

[0125] Thus, this invention enables advanced opinion gathering and analysis using an emotion engine, allowing for the formulation of urban plans that more accurately reflect the intentions of residents. This contributes to the sustainable development of local communities.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The server collects demographic data and resident opinion submission data through open data from local governments and social media APIs, and stores it in a database. At this time, the data is organized in an appropriate format to prepare it for subsequent processing.

[0129] Step 2:

[0130] The terminal receives opinions and suggestions from residents through its user interface. When a user inputs information, the terminal's built-in emotion engine acquires emotional data from the user's facial expressions and voice.

[0131] Step 3:

[0132] Users input their opinions and suggestions through their devices and add comments as needed. This information, along with sentiment data collected by the sentiment engine, is immediately sent to the server.

[0133] Step 4:

[0134] The server analyzes the received user opinions and sentiment data using information processing tools. By analyzing sentiment trends, it understands the emotional responses behind residents' opinions and uses this information in urban planning. The analysis results are visualized on a dashboard and made available to stakeholders.

[0135] Step 5:

[0136] The device provides a simulation environment that allows users to experience urban planning proposals using virtual reality or augmented reality technology. Users can experience the plan within this virtual environment and resubmit their feedback based on the visualized results.

[0137] Step 6:

[0138] The emotional changes the user exhibits during the experience are again collected by the device's emotion engine. This feedback data is also sent to the server and analyzed immediately.

[0139] Step 7:

[0140] The server uses newly acquired emotional feedback to identify areas for adjustment and improvement in the plan. It generates an optimized plan that reflects the user's emotions and notifies stakeholders of the update via the dashboard.

[0141] Step 8:

[0142] The server provides analytical data to external developers via open APIs, supporting the development of new features and improvement tools. This provision allows various solutions to be applied to address region-specific challenges.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] Modern urban planning requires not only gathering user opinions but also conducting analyses from diverse perspectives that take emotions into account. However, conventional systems have struggled to efficiently analyze emotional states and reflect them in planning in real time. Therefore, there is a need for efficient methods to quickly and accurately formulate beneficial urban plans.

[0146] 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.

[0147] In this invention, the server includes a human interface means for collecting user opinions and emotional states, an information processing means for analyzing the collected data and formulating urban plans using a generative AI model, and a display means for visualizing the plan proposal based on the analyzed opinion and emotional data and enabling simulation in a virtual environment. This makes it possible to formulate sophisticated and intuitive urban plans that include emotions.

[0148] "Human interface means" refers to devices or software for users to input their opinions and emotional states, and the data collected through these means forms the basis for analysis.

[0149] "Information processing means" refers to systems and algorithms that analyze collected opinion and sentiment data and use generative AI models to formulate urban plans.

[0150] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to predict and generate optimal urban planning proposals from opinion and sentiment data.

[0151] "Display means" refers to a device or computer program that visualizes analysis and simulation results and helps users easily understand them, and may utilize virtual reality or augmented reality technologies.

[0152] A "virtual environment" refers to a computer-generated environment used to visually simulate a plan, allowing users to experience situations and spaces that do not actually exist.

[0153] "Data communication methods" refer to infrastructure and protocols used to transmit collected opinion and sentiment data to servers in real time for use in coordinating urban planning.

[0154] This invention provides a system that comprehensively handles everything from opinion gathering and analysis to simulation in a virtual environment, in order to formulate sophisticated and rapid urban plans. This system mainly consists of servers, terminals, and users, each of which works in conjunction with the others.

[0155] The server first collects opinions and comments from local governments and online social platforms via APIs. Common web scraping tools and API clients are used for this data collection. Next, the server organizes and stores the collected data in a database. General SQL database management systems and NoSQL databases are suitable for database management.

[0156] The server uses a generative AI model to analyze the collected data. This generative AI model extracts emotional data from opinions and incorporates it into urban planning proposals. Natural language processing techniques are employed in this analysis, specifically an AI algorithm implemented to identify emotions from text.

[0157] The terminal provides an interface for users to input their opinions and simultaneously collects emotional data expressed during the input process. At this stage, real-time data transmission and secure communication protocols are crucial, and technologies such as WebSocket are used.

[0158] Furthermore, the device provides users with a means to visualize urban planning proposals using virtual reality (VR) and augmented reality (AR). This allows users to experience a virtual environment of the plan and provide specific feedback. Technologies supporting this process include VR / AR platforms, such as engines like Unity.

[0159] Through their experience in a virtual environment, users provide emotional feedback to the proposed plan via their devices, sending it back to the server. This allows the urban planning proposal to be adjusted in real time, more accurately reflecting the intentions of the residents.

[0160] An example of this system's use is a design plan for a new park. The server analyzes residents' opinions and feelings about the plan and adjusts its direction based on indicators of safety and enjoyment. An example of a prompt might be, "Please tell me how to analyze residents' expectations and concerns regarding the design of the new park and adjust the direction of the plan."

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The server collects opinion data through municipal databases and online platform APIs. This input data consists of opinions and comments in text format, which the server stores in its database. Specific scraping tools and API clients are used for data collection. For example, text data is input, and structured data is stored in the database as a result.

[0164] Step 2:

[0165] The server analyzes the collected opinion data using a generative AI model. The structured data saved in step 1 is taken in as input. The server uses the generative AI model to detect and classify emotions in the data and generate insights that can be used in urban planning. As a result, new analyzed emotion data is obtained.

[0166] Step 3:

[0167] The terminal receives opinions and emotional states directly from the user as input through a human interface. At this time, the terminal collects data in real time through the user interface and transmits it to the server. Real-time input data includes the user's opinions and intuitive feedback. The output is raw data that is immediately transmitted to the server.

[0168] Step 4:

[0169] The server re-analyzes the real-time sentiment data collected in step 3. This input data includes immediate feedback from users. The server integrates this real-time data into the existing plan and adjusts the urban planning proposal. As a result, a new urban planning proposal that reflects the users' sentiment data is output.

[0170] Step 5:

[0171] The terminal uses virtual reality and augmented reality technologies to present the generated urban planning proposal to the user. The input is the urban planning proposal generated in step 4. The terminal visually simulates the proposal and sets it up so that the user can experience a concrete space and situation. As a result, a visually represented proposal is provided to the user.

[0172] Step 6:

[0173] Users provide feedback based on their experiences in the virtual environment. Input includes judgments and emotions based on the user's experience. The terminal then sends this feedback back to the server, which is used to further refine the urban plan. Output is the transmission of user feedback data to the server.

[0174] (Application Example 2)

[0175] 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".

[0176] While resident participation is crucial in urban development planning, traditional methods often fail to adequately reflect residents' opinions and feelings, impacting the success or failure of the plan. Furthermore, real-time collection of opinions and understanding emotional states are difficult, hindering flexible adjustments to the plan.

[0177] 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.

[0178] In this invention, the server includes a user interface means for collecting user opinions and behavioral states, a data processing means for integrating the collected data and analyzed behavioral data to formulate a settlement plan, a visualization means for visualizing the analysis results and enabling a behavioral prediction experience in a virtual environment, and an open-source means for enabling collaboration with multiple participants. This makes it possible to collect residents' opinions and feelings in real time and formulate flexible urban plans that reflect them in the plan.

[0179] "User interface means" refers to input devices or software used to collect data on opinions and behavioral states from users.

[0180] "Data processing means" refers to an information processing device or software used to analyze and integrate collected opinion data and behavioral data in order to formulate a community plan.

[0181] "Visualization means" refers to a display device or software that visually displays the analyzed data results and allows users to experience behavioral prediction in a virtual environment.

[0182] "Open source methods" refer to techniques that involve releasing source code and APIs in order to expand and improve a system through collaboration among multiple participants and developers.

[0183] To implement this invention, a system is constructed in which a server, a terminal, and a user cooperate. The server collects user opinions and behavioral states in real time and analyzes them using data processing means. Specifically, the "TextBlob" library in Python is used to perform text analysis on emotional data, and software such as "Unity" and "ARKit / ARCore" are used for the virtual reality experience.

[0184] The terminal is envisioned as hardware such as smartphones and tablets, and is equipped with a user interface. Here, an application is implemented that allows residents to input their opinions, and is configured to collect their emotional states at the same time. Furthermore, as a means of visualization, users are provided with a virtual community planning experience, enabling them to predict their own behavior.

[0185] Users experience the visualized plan in virtual reality via an application on their device. The opinions and emotional states gained through this experience are shared with other participants through open-source means and used to improve the plan.

[0186] One concrete example is a residential area improvement plan, where users can virtually walk around the area through the app and send their impressions and opinions in real time. An example of a prompt message would be, "Please tell us in detail what you felt and where you felt after experiencing the new park design plan in virtual reality."

[0187] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0188] Step 1:

[0189] The device receives input from the user regarding opinions and emotional states via a user interface. This input includes opinions in text format and emotional state data obtained from sensors. The device temporarily stores this data and sends it to the server.

[0190] Step 2:

[0191] The server analyzes opinion and emotional state data received from the terminal. Here, the Python library "TextBlob" is used for text sentiment analysis. The input opinion data is classified into emotional categories such as positive, negative, and neutral. These results are stored in a database.

[0192] Step 3:

[0193] The server uses data processing tools to formulate a settlement plan. It incorporates previously analyzed opinion and sentiment data and uses a generative AI model to analyze the overall residents' evaluation. This results in the output of a plan that reflects the residents' opinions and sentiments.

[0194] Step 4:

[0195] The server uses visualization tools to visualize the drafted plan. To provide a virtual reality experience, it utilizes Unity and ARKit / ARCore to generate a three-dimensional environment. This environment data is then sent back to the terminal.

[0196] Step 5:

[0197] Users experience a settlement plan generated in virtual reality using their device. During this experience, users can input new opinions, and their emotional state is continuously detected by sensors and immediately sent back to the server. This process enables real-time adjustment of the plan.

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

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

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

[0201] [Second Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0214] This invention is a system for collecting residents' opinions and incorporating them into urban planning in order to support the sustainable development of local communities. The system operates primarily around three elements: a server, terminals, and users, and aims to improve the efficiency of urban planning through effective cooperation between them.

[0215] The server uses a data collection module to gather diverse data from local governments and social media in real time and store it in a dedicated database. This data includes multifaceted information such as local demographics and the latest opinions of residents.

[0216] Furthermore, the server uses advanced information processing tools to analyze the collected data. Using sophisticated machine learning algorithms, it predicts population growth and decline, as well as economic trends. The results of this analysis are visualized on a dashboard and provided to terminal users via their devices.

[0217] The terminal functions as an interface between residents and the local government, providing a user interface for residents to access. Through this interface, users can submit their opinions and proposed plans. These opinions are sent to the server and incorporated into the analysis.

[0218] The terminal also features display methods that utilize virtual environments and augmented reality technology. This allows users to visually confirm simulations based on their proposals and intuitively understand the impact of their plans.

[0219] Furthermore, the server provides an open API, allowing external developers to add new functionality to the system. The open API facilitates smooth data exchange between the server and external programs. This creates an environment where residents, local businesses, and universities can collaborate to develop solutions that address region-specific challenges.

[0220] As a concrete example, in areas with an aging population, a server identifies the increasing trend of elderly people through data analysis. Using terminals, feedback is received from residents, and simulations are conducted to improve the design of public facilities based on that feedback. As a result, efficient and livable urban design becomes possible.

[0221] This invention aims to realize flexible and sustainable urban planning by incorporating a community-based, resident-participatory approach into the system.

[0222] The following describes the processing flow.

[0223] Step 1:

[0224] The server collects demographic and environmental data from open data sources provided by local governments and stores it in a database. It also obtains residents' opinions and trend data in real time through social media APIs.

[0225] Step 2:

[0226] The server cleanses the collected data, removing unnecessary data and imputing missing values. The data is then formatted to a format suitable for analysis.

[0227] Step 3:

[0228] The server uses machine learning algorithms to predict demographic and economic trends and generate analysis results. This allows for the evaluation of future changes and their incorporation into planning.

[0229] Step 4:

[0230] The terminal provides a user interface for resident participation. Through this interface, users can input suggestions and opinions regarding urban planning.

[0231] Step 5:

[0232] The server receives opinion data from residents and incorporates it as part of the data analysis. The analysis results, which take residents' opinions into account, are displayed on a dashboard.

[0233] Step 6:

[0234] The device runs simulations using VR or AR technology, allowing users to experience proposed urban planning changes in a virtual space. Through this experience, users can participate in optimizing the plan.

[0235] Step 7:

[0236] The server provides data access to external developers through open APIs, supporting the development of additional features and new tools. This facilitates the development of region-specific solutions.

[0237] (Example 1)

[0238] 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."

[0239] Modern urban planning not only struggles to adequately reflect the opinions of local communities, but also requires rapid responses to predicted demographic changes and technological advancements. However, traditional methods struggle with rapid and accurate data collection and analysis, and the environment for diverse stakeholders to collaborate and expand functionality is not adequately developed. New tools are needed to improve this situation and realize sustainable urban planning.

[0240] 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.

[0241] In this invention, the server includes data processing means for collecting and analyzing data, a display device for visualizing the analyzed information and enabling simulations in a virtual space, and a public API means for enabling collaboration with multiple engineers. This makes it possible to collect opinions from local residents in real time, predict demographic changes, and conduct planning simulations in a virtual space, while developing sustainable urban plans optimized for the region through collaboration with diverse stakeholders.

[0242] A "human interface means" is a means by which users input opinions into a system and obtain information.

[0243] "Data processing means" refers to means for analyzing collected data and extracting relevant information.

[0244] A "display device" is a means of visualizing analyzed information in the form of graphics or videos and presenting it in a way that is easy for users to understand.

[0245] A "public API means" is a means of providing an interface that allows external engineers to add new functions to a system or utilize existing data.

[0246] A "machine learning algorithm" is an algorithm that learns patterns and trends from large amounts of data to predict future population trends and economic conditions.

[0247] "External platform integration means" refers to means for exchanging data with other systems and applications and extending their functionality.

[0248] This invention is an urban planning system designed to support the sustainable development of local communities. The system primarily consists of three elements: a server, terminals, and users.

[0249] The server utilizes a data collection module to collect data in real time from local governments and online platforms. The data is automatically recorded in a dedicated database via an API over the internet. The collected information includes residents' opinions, demographic trends, and economic indicators. The server then analyzes the data using machine learning algorithms written in programming languages ​​such as Python and R. This makes it possible to predict future population trends and socioeconomic trends. The analysis results are displayed on a dashboard using visualization tools and sent to the user's device.

[0250] The terminal functions as an interface with residents and local government officials. Users can directly input their opinions and suggestions using the interface provided on the terminal. This information is sent to a server and used for analysis. The terminal also features display functions using virtual reality (VR) and augmented reality (AR) technologies. This allows for the visual presentation of simulations based on suggestions, and users can see the impact in real time. For example, by using a VR headset or an AR application on a smartphone, users can experience future urban design.

[0251] Users can submit opinions to the system via their devices and receive feedback. This enables community-participatory urban planning. Users can also view the provided simulations, develop new proposals, and input them back into the system. This process allows for flexible urban planning based on the diverse needs of the community.

[0252] As a concrete example, in areas with an aging population, a server performs data analysis to identify an increasing trend in residents aged 60 and over. Opinions on improving access to public facilities are collected from residents via terminals, and simulations based on these opinions are provided on the terminals. This allows residents to virtually try out the improvement proposals they have made. An example of a prompt for the generated AI model is, "Please create a proposal for sustainable urban planning based on local demographics and residents' opinions. Please include ideas for design improvements to public facilities in areas with an aging population."

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

[0254] Step 1:

[0255] The server collects data from local governments and online platforms via APIs. The data received as input includes residents' opinions, local demographics, and economic activity information. Storing this data in a dedicated database enables real-time information updates. Specifically, a program operates that periodically collects publicly available data from local governments and feeds from social media via a network connection.

[0256] Step 2:

[0257] The server inputs the collected data into a machine learning algorithm for analysis. This process classifies and aggregates the information to predict demographic trends and identify trends in economic activity. The output includes predictions of future trends and regional opinion tendencies. Specifically, statistical analysis libraries such as Python are used to train and infer the model.

[0258] Step 3:

[0259] The server visualizes the analysis results in a dashboard format and sends them to the terminal. The input is the analyzed data, and the output is visualized graphs and charts. Specifically, it uses data visualization tools to graphically transform the data and delivers it to the terminal via a web interface.

[0260] Step 4:

[0261] The terminal displays visualized data in a user interface. Users view this, intuitively understand the information, and input their own opinions. In this step, resident feedback is added as user input, which is then incorporated into the next data collection cycle. Specifically, the terminal accepts user input via a touchscreen or keyboard and sends it to a server.

[0262] Step 5:

[0263] The device uses virtual and augmented reality to provide a simulation of urban planning based on user proposals. The input is the user's proposal, and the output is a simulated urban environment. Specifically, the device generates a virtual model using a 3D graphics engine and performs the simulation via a VR / AR device.

[0264] Step 6:

[0265] The server allows external engineers to add functionality to the system through an open API. The input is a new external program, and the output is a system with extensions that integrate that program. Specifically, it processes API requests, stores the results in a database, and applies them to the entire system.

[0266] This series of steps enables the collection of community opinions in a readily accessible format in real time, and allows for sustainable urban planning based on data analysis.

[0267] (Application Example 1)

[0268] 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."

[0269] In urban planning aimed at the sustainable development of local communities, it is crucial to effectively collect and reflect the diverse opinions of residents. However, traditional systems have suffered from problems such as insufficient visibility of residents' proposals and difficulties in smooth communication between planners and residents. Furthermore, the lack of means to promote residents' intuitive understanding of new urban planning proposals has hindered the effective implementation of plans.

[0270] 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.

[0271] In this invention, the server includes a human interface means for collecting user opinions, an information processing means for analyzing the collected data and formulating urban plans, a display means for visualizing the analysis results and enabling simulation of user proposals in a virtual environment, and a means for providing visual feedback on the plan using augmented reality technology. This makes it possible to intuitively understand residents' proposals and to communicate smoothly with planners.

[0272] "Human interface means for collecting opinions" refers to communication technologies and devices for obtaining feedback and suggestions from users in real time.

[0273] "Information processing tools for analyzing data and formulating urban plans" refer to algorithms and computer programs that automatically generate plans for urban development and problem solving based on collected data.

[0274] "A display means that visualizes analysis results and enables user proposals to be simulated in a virtual environment" refers to a technological device that graphically represents the results of data analysis and enables users to test their proposed plans in a virtual environment.

[0275] "Means of providing visual feedback on plans using augmented reality technology" refers to devices or software that utilize augmented reality technology to visually present a proposed plan to the user in a way that overlays it onto the real world, thereby facilitating understanding.

[0276] "Development support tools" refer to technical foundations and platforms that enable multiple developers to collaborate in adding or improving new features to a system.

[0277] The system for implementing this invention has the following configuration in order to contribute to the sustainable development of the local community.

[0278] The server utilizes a cloud computing platform with advanced data analysis capabilities to collect users' opinions and perform real-time data processing for urban planning. For this purpose, it uses Google Cloud Platform's machine learning tools to collect diverse data from local governments and social media and store it in Firebase. Machine learning algorithms are applied for analysis to predict population trends and economic trends in the region. The analysis results are visualized on a dashboard and provided to users.

[0279] The terminal serves as an interface for residents to access and is equipped with a cross-platform application developed in React Native. Users can use this application to easily submit their opinions and suggestions. These opinions are sent to the server and utilized for analysis.

[0280] Also, as a simulation means using augmented reality technology, the Unity engine and AR Foundation are used. This enables users to visualize their proposed urban plans in a virtual environment and intuitively confirm them. For example, submit a proposal for a new park and view the completed image in AR.

[0281] As a specific example, it is possible to propose a design plan for a multi-purpose square where the elderly can gather in an aging area. An example of a prompt sentence to input into the generative AI model is "I have submitted a design plan for a multi-purpose square for the elderly. I would like to view the completed image in AR."

[0282] In this way, the system can directly reflect residents' opinions in urban planning and promote communication between residents and planners.

[0283] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0284] Step 1:

[0285] The user inputs opinions and suggestions via the terminal. The input data is sent to the server through the human interface means. Here, the input is the user's opinions and suggestion content, and as output, data packets based on it are sent to the server.

[0286] Step 2:

[0287] The server saves the received opinions and suggestions in Google Firebase. Here, the input is the data packet sent in Step 1, and the output is the completion status of saving to the database. The saved data will be the target of subsequent analysis processing.

[0288] Step 3:

[0289] The server analyzes the saved data using the machine learning tools of Google Cloud Platform. Here, the input is the user's opinions and urban data saved in the database, and the output obtained by the analysis is the prediction results of population trends and economic trends. This analysis is performed by combining data processing and machine learning algorithms.

[0290] Step 4:

[0291] The server visualizes the analysis results on the dashboard and sends them to the terminal. The input is the analysis results, and the output is the visualized data. Through this data, the user can check the prediction results of the proposed urban plan.

[0292] Step 5:

[0293] [[ID=3l]] The user utilizes the Unity engine and AR Foundation through the application used on the terminal to execute a virtual simulation based on the proposal. Here, the input is the user's proposal and visualization data, and the output is the visual feedback in the AR environment. Through this operation, the user can intuitively understand the feasibility and impact of the proposal.

[0294] 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.

[0295] This invention provides an urban planning system that considers not only the opinions of residents but also their emotional states. This enables a more sophisticated form of resident-participatory planning. The system consists of three elements: a server, terminals, and users, and their roles are interconnected.

[0296] The server first has the function of collecting data from local governments and social media, and this data is stored in a database. It also has an information processing system equipped with an emotion engine, which allows it to analyze the emotional state of users. The server uses this emotion data to supplement the information on the background in which residents' opinions were submitted and to perform a more detailed analysis.

[0297] The terminal provides a means for residents to input opinions and suggestions through a user interface. In addition, the terminal works in conjunction with an emotion engine to collect emotional data expressed by users during their interaction with the interface. This emotional data is immediately transmitted to a server and recorded in a database.

[0298] The server analyzes emotional data during the information processing process and generates urban planning proposals that take this into account. The analysis results are displayed on a dashboard and provided in a visually easy-to-understand format for users. By analyzing emotional data, it is also possible to pre-evaluate the level of public acceptance of the plan.

[0299] Furthermore, the device is equipped with display methods that utilize virtual reality and augmented reality. Users can experience the proposed plan in a virtual environment, and the emotional changes they experience are analyzed again by an emotion engine and sent to the server as immediate feedback. This allows for real-time adjustments to the urban plan.

[0300] As a specific example considering emotions, in a new park design plan, the server analyzes emotional data such as the sense of expectation and concern towards the plan, along with the opinions of residents. During the simulation experience using the terminal, if the user feels enjoyment or a sense of security, the direction of the plan can be finely adjusted accordingly.

[0301] Thus, according to the present invention, advanced opinion collection and analysis utilizing an emotion engine become possible, and an urban plan that more accurately reflects the intentions of residents can be formulated. This contributes to the sustainable development of the local community.

[0302] The processing flow will be described below.

[0303] Step 1:

[0304] The server collects population dynamics data and residents' opinion submission data through the open data of the local government and social media APIs, and stores them in a database. At this time, the data is organized in an appropriate format to prepare for subsequent processing.

[0305] Step 2:

[0306] The terminal receives opinions and proposals from residents via the user interface. When the user inputs, the emotion engine installed on the terminal acquires emotional data from the user's expression and voice.

[0307] Step 3:

[0308] The user inputs their opinions and proposals through the terminal and adds comments if necessary. This information and the emotional data collected by the emotion engine are immediately sent to the server.

[0309] Step 4:

[0310] The server analyzes the received user opinions and sentiment data using information processing tools. By analyzing sentiment trends, it understands the emotional responses behind residents' opinions and uses this information in urban planning. The analysis results are visualized on a dashboard and made available to stakeholders.

[0311] Step 5:

[0312] The device provides a simulation environment that allows users to experience urban planning proposals using virtual reality or augmented reality technology. Users can experience the plan within this virtual environment and resubmit their feedback based on the visualized results.

[0313] Step 6:

[0314] The emotional changes the user exhibits during the experience are again collected by the device's emotion engine. This feedback data is also sent to the server and analyzed immediately.

[0315] Step 7:

[0316] The server uses newly acquired emotional feedback to identify areas for adjustment and improvement in the plan. It generates an optimized plan that reflects the user's emotions and notifies stakeholders of the update via the dashboard.

[0317] Step 8:

[0318] The server provides analytical data to external developers via open APIs, supporting the development of new features and improvement tools. This provision allows various solutions to be applied to address region-specific challenges.

[0319] (Example 2)

[0320] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0321] Modern urban planning requires not only gathering user opinions but also conducting analyses from diverse perspectives that take emotions into account. However, conventional systems have struggled to efficiently analyze emotional states and reflect them in planning in real time. Therefore, there is a need for efficient methods to quickly and accurately formulate beneficial urban plans.

[0322] 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.

[0323] In this invention, the server includes a human interface means for collecting user opinions and emotional states, an information processing means for analyzing the collected data and formulating urban plans using a generative AI model, and a display means for visualizing the plan proposal based on the analyzed opinion and emotional data and enabling simulation in a virtual environment. This makes it possible to formulate sophisticated and intuitive urban plans that include emotions.

[0324] "Human interface means" refers to devices or software for users to input their opinions and emotional states, and the data collected through these means forms the basis for analysis.

[0325] "Information processing means" refers to systems and algorithms that analyze collected opinion and sentiment data and use generative AI models to formulate urban plans.

[0326] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to predict and generate optimal urban planning proposals from opinion and sentiment data.

[0327] "Display means" refers to a device or computer program that visualizes analysis and simulation results and helps users easily understand them, and may utilize virtual reality or augmented reality technologies.

[0328] A "virtual environment" refers to a computer-generated environment used to visually simulate a plan, allowing users to experience situations and spaces that do not actually exist.

[0329] "Data communication methods" refer to infrastructure and protocols used to transmit collected opinion and sentiment data to servers in real time for use in coordinating urban planning.

[0330] This invention provides a system that comprehensively handles everything from opinion gathering and analysis to simulation in a virtual environment, in order to formulate sophisticated and rapid urban plans. This system mainly consists of servers, terminals, and users, each of which works in conjunction with the others.

[0331] The server first collects opinions and comments from local governments and online social platforms via APIs. Common web scraping tools and API clients are used for this data collection. Next, the server organizes and stores the collected data in a database. General SQL database management systems and NoSQL databases are suitable for database management.

[0332] The server uses a generative AI model to analyze the collected data. This generative AI model extracts emotional data from opinions and incorporates it into urban planning proposals. Natural language processing techniques are employed in this analysis, specifically an AI algorithm implemented to identify emotions from text.

[0333] The terminal provides an interface for users to input their opinions and simultaneously collects emotional data expressed during the input process. At this stage, real-time data transmission and secure communication protocols are crucial, and technologies such as WebSocket are used.

[0334] Furthermore, the device provides users with a means to visualize urban planning proposals using virtual reality (VR) and augmented reality (AR). This allows users to experience a virtual environment of the plan and provide specific feedback. Technologies supporting this process include VR / AR platforms, such as engines like Unity.

[0335] Through their experience in a virtual environment, users provide emotional feedback to the proposed plan via their devices, sending it back to the server. This allows the urban planning proposal to be adjusted in real time, more accurately reflecting the intentions of the residents.

[0336] An example of this system's use is a design plan for a new park. The server analyzes residents' opinions and feelings about the plan and adjusts its direction based on indicators of safety and enjoyment. An example of a prompt might be, "Please tell me how to analyze residents' expectations and concerns regarding the design of the new park and adjust the direction of the plan."

[0337] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0338] Step 1:

[0339] The server collects opinion data through municipal databases and online platform APIs. This input data consists of opinions and comments in text format, which the server stores in its database. Specific scraping tools and API clients are used for data collection. For example, text data is input, and structured data is stored in the database as a result.

[0340] Step 2:

[0341] The server analyzes the collected opinion data using a generative AI model. The structured data saved in step 1 is taken in as input. The server uses the generative AI model to detect and classify emotions in the data and generate insights that can be used in urban planning. As a result, new analyzed emotion data is obtained.

[0342] Step 3:

[0343] The terminal receives opinions and emotional states directly from the user as input through a human interface. At this time, the terminal collects data in real time through the user interface and transmits it to the server. Real-time input data includes the user's opinions and intuitive feedback. The output is raw data that is immediately transmitted to the server.

[0344] Step 4:

[0345] The server re-analyzes the real-time sentiment data collected in step 3. This input data includes immediate feedback from users. The server integrates this real-time data into the existing plan and adjusts the urban planning proposal. As a result, a new urban planning proposal that reflects the users' sentiment data is output.

[0346] Step 5:

[0347] The terminal uses virtual reality and augmented reality technologies to present the generated urban planning proposal to the user. The input is the urban planning proposal generated in step 4. The terminal visually simulates the proposal and sets it up so that the user can experience a concrete space and situation. As a result, a visually represented proposal is provided to the user.

[0348] Step 6:

[0349] Users provide feedback based on their experiences in the virtual environment. Input includes judgments and emotions based on the user's experience. The terminal then sends this feedback back to the server, which is used to further refine the urban plan. Output is the transmission of user feedback data to the server.

[0350] (Application Example 2)

[0351] 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."

[0352] While resident participation is crucial in urban development planning, traditional methods often fail to adequately reflect residents' opinions and feelings, impacting the success or failure of the plan. Furthermore, real-time collection of opinions and understanding emotional states are difficult, hindering flexible adjustments to the plan.

[0353] 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.

[0354] In this invention, the server includes a user interface means for collecting user opinions and behavioral states, a data processing means for integrating the collected data and analyzed behavioral data to formulate a settlement plan, a visualization means for visualizing the analysis results and enabling a behavioral prediction experience in a virtual environment, and an open-source means for enabling collaboration with multiple participants. This makes it possible to collect residents' opinions and feelings in real time and formulate flexible urban plans that reflect them in the plan.

[0355] "User interface means" refers to input devices or software used to collect data on opinions and behavioral states from users.

[0356] "Data processing means" refers to an information processing device or software used to analyze and integrate collected opinion data and behavioral data in order to formulate a community plan.

[0357] "Visualization means" refers to a display device or software that visually displays the analyzed data results and allows users to experience behavioral prediction in a virtual environment.

[0358] "Open source methods" refer to techniques that involve releasing source code and APIs in order to expand and improve a system through collaboration among multiple participants and developers.

[0359] To implement this invention, a system is constructed in which a server, a terminal, and a user cooperate. The server collects user opinions and behavioral states in real time and analyzes them using data processing means. Specifically, the "TextBlob" library in Python is used to perform text analysis on emotional data, and software such as "Unity" and "ARKit / ARCore" are used for the virtual reality experience.

[0360] The terminal is envisioned as hardware such as smartphones and tablets, and is equipped with a user interface. Here, an application is implemented that allows residents to input their opinions, and is configured to collect their emotional states at the same time. Furthermore, as a means of visualization, users are provided with a virtual community planning experience, enabling them to predict their own behavior.

[0361] Users experience the visualized plan in virtual reality via an application on their device. The opinions and emotional states gained through this experience are shared with other participants through open-source means and used to improve the plan.

[0362] One concrete example is a residential area improvement plan, where users can virtually walk around the area through the app and send their impressions and opinions in real time. An example of a prompt message would be, "Please tell us in detail what you felt and where you felt after experiencing the new park design plan in virtual reality."

[0363] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0364] Step 1:

[0365] The device receives input from the user regarding opinions and emotional states via a user interface. This input includes opinions in text format and emotional state data obtained from sensors. The device temporarily stores this data and sends it to the server.

[0366] Step 2:

[0367] The server analyzes opinion and emotional state data received from the terminal. Here, the Python library "TextBlob" is used for text sentiment analysis. The input opinion data is classified into emotional categories such as positive, negative, and neutral. These results are stored in a database.

[0368] Step 3:

[0369] The server uses data processing tools to formulate a settlement plan. It incorporates previously analyzed opinion and sentiment data and uses a generative AI model to analyze the overall residents' evaluation. This results in the output of a plan that reflects the residents' opinions and sentiments.

[0370] Step 4:

[0371] The server uses visualization tools to visualize the drafted plan. To provide a virtual reality experience, it utilizes Unity and ARKit / ARCore to generate a three-dimensional environment. This environment data is then sent back to the terminal.

[0372] Step 5:

[0373] Users experience a settlement plan generated in virtual reality using their device. During this experience, users can input new opinions, and their emotional state is continuously detected by sensors and immediately sent back to the server. This process enables real-time adjustment of the plan.

[0374] 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.

[0375] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0376] 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.

[0377] [Third Embodiment]

[0378] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0379] 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.

[0380] 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).

[0381] 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.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] 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".

[0390] This invention is a system for collecting residents' opinions and incorporating them into urban planning in order to support the sustainable development of local communities. The system operates primarily around three elements: a server, terminals, and users, and aims to improve the efficiency of urban planning through effective cooperation between them.

[0391] The server uses a data collection module to gather diverse data from local governments and social media in real time and store it in a dedicated database. This data includes multifaceted information such as local demographics and the latest opinions of residents.

[0392] Furthermore, the server uses advanced information processing tools to analyze the collected data. Using sophisticated machine learning algorithms, it predicts population growth and decline, as well as economic trends. The results of this analysis are visualized on a dashboard and provided to terminal users via their devices.

[0393] The terminal functions as an interface between residents and the local government, providing a user interface for residents to access. Through this interface, users can submit their opinions and proposed plans. These opinions are sent to the server and incorporated into the analysis.

[0394] The terminal also features display methods that utilize virtual environments and augmented reality technology. This allows users to visually confirm simulations based on their proposals and intuitively understand the impact of their plans.

[0395] Furthermore, the server provides an open API, allowing external developers to add new functionality to the system. The open API facilitates smooth data exchange between the server and external programs. This creates an environment where residents, local businesses, and universities can collaborate to develop solutions that address region-specific challenges.

[0396] As a concrete example, in areas with an aging population, a server identifies the increasing trend of elderly people through data analysis. Using terminals, feedback is received from residents, and simulations are conducted to improve the design of public facilities based on that feedback. As a result, efficient and livable urban design becomes possible.

[0397] This invention aims to realize flexible and sustainable urban planning by incorporating a community-based, resident-participatory approach into the system.

[0398] The following describes the processing flow.

[0399] Step 1:

[0400] The server collects demographic and environmental data from open data sources provided by local governments and stores it in a database. It also obtains residents' opinions and trend data in real time through social media APIs.

[0401] Step 2:

[0402] The server cleanses the collected data, removing unnecessary data and imputing missing values. The data is then formatted to a format suitable for analysis.

[0403] Step 3:

[0404] The server uses machine learning algorithms to predict demographic and economic trends and generate analysis results. This allows for the evaluation of future changes and their incorporation into planning.

[0405] Step 4:

[0406] The terminal provides a user interface for resident participation. Through this interface, users can input suggestions and opinions regarding urban planning.

[0407] Step 5:

[0408] The server receives opinion data from residents and incorporates it as part of the data analysis. The analysis results, which take residents' opinions into account, are displayed on a dashboard.

[0409] Step 6:

[0410] The device runs simulations using VR or AR technology, allowing users to experience proposed urban planning changes in a virtual space. Through this experience, users can participate in optimizing the plan.

[0411] Step 7:

[0412] The server provides data access to external developers through open APIs, supporting the development of additional features and new tools. This facilitates the development of region-specific solutions.

[0413] (Example 1)

[0414] 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."

[0415] Modern urban planning not only struggles to adequately reflect the opinions of local communities, but also requires rapid responses to predicted demographic changes and technological advancements. However, traditional methods struggle with rapid and accurate data collection and analysis, and the environment for diverse stakeholders to collaborate and expand functionality is not adequately developed. New tools are needed to improve this situation and realize sustainable urban planning.

[0416] 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.

[0417] In this invention, the server includes data processing means for collecting and analyzing data, a display device for visualizing the analyzed information and enabling simulations in a virtual space, and a public API means for enabling collaboration with multiple engineers. This makes it possible to collect opinions from local residents in real time, predict demographic changes, and conduct planning simulations in a virtual space, while developing sustainable urban plans optimized for the region through collaboration with diverse stakeholders.

[0418] A "human interface means" is a means by which users input opinions into a system and obtain information.

[0419] "Data processing means" refers to means for analyzing collected data and extracting relevant information.

[0420] A "display device" is a means of visualizing analyzed information in the form of graphics or videos and presenting it in a way that is easy for users to understand.

[0421] A "public API means" is a means of providing an interface that allows external engineers to add new functions to a system or utilize existing data.

[0422] A "machine learning algorithm" is an algorithm that learns patterns and trends from large amounts of data to predict future population trends and economic conditions.

[0423] "External platform integration means" refers to means for exchanging data with other systems and applications and extending their functionality.

[0424] This invention is an urban planning system designed to support the sustainable development of local communities. The system primarily consists of three elements: a server, terminals, and users.

[0425] The server utilizes a data collection module to collect data in real time from local governments and online platforms. The data is automatically recorded in a dedicated database via an API over the internet. The collected information includes residents' opinions, demographic trends, and economic indicators. The server then analyzes the data using machine learning algorithms written in programming languages ​​such as Python and R. This makes it possible to predict future population trends and socioeconomic trends. The analysis results are displayed on a dashboard using visualization tools and sent to the user's device.

[0426] The terminal functions as an interface with residents and local government officials. Users can directly input their opinions and suggestions using the interface provided on the terminal. This information is sent to a server and used for analysis. The terminal also features display functions using virtual reality (VR) and augmented reality (AR) technologies. This allows for the visual presentation of simulations based on suggestions, and users can see the impact in real time. For example, by using a VR headset or an AR application on a smartphone, users can experience future urban design.

[0427] Users can submit opinions to the system via their devices and receive feedback. This enables community-participatory urban planning. Users can also view the provided simulations, develop new proposals, and input them back into the system. This process allows for flexible urban planning based on the diverse needs of the community.

[0428] As a concrete example, in areas with an aging population, a server performs data analysis to identify an increasing trend in residents aged 60 and over. Opinions on improving access to public facilities are collected from residents via terminals, and simulations based on these opinions are provided on the terminals. This allows residents to virtually try out the improvement proposals they have made. An example of a prompt for the generated AI model is, "Please create a proposal for sustainable urban planning based on local demographics and residents' opinions. Please include ideas for design improvements to public facilities in areas with an aging population."

[0429] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0430] Step 1:

[0431] The server collects data from local governments and online platforms via APIs. The data received as input includes residents' opinions, local demographics, and economic activity information. Storing this data in a dedicated database enables real-time information updates. Specifically, a program operates that periodically collects publicly available data from local governments and feeds from social media via a network connection.

[0432] Step 2:

[0433] The server inputs the collected data into a machine learning algorithm for analysis. This process classifies and aggregates the information to predict demographic trends and identify trends in economic activity. The output includes predictions of future trends and regional opinion tendencies. Specifically, statistical analysis libraries such as Python are used to train and infer the model.

[0434] Step 3:

[0435] The server visualizes the analysis results in a dashboard format and sends them to the terminal. The input is the analyzed data, and the output is visualized graphs and charts. Specifically, it uses data visualization tools to graphically transform the data and delivers it to the terminal via a web interface.

[0436] Step 4:

[0437] The terminal displays visualized data in a user interface. Users view this, intuitively understand the information, and input their own opinions. In this step, resident feedback is added as user input, which is then incorporated into the next data collection cycle. Specifically, the terminal accepts user input via a touchscreen or keyboard and sends it to a server.

[0438] Step 5:

[0439] The device uses virtual and augmented reality to provide a simulation of urban planning based on user proposals. The input is the user's proposal, and the output is a simulated urban environment. Specifically, the device generates a virtual model using a 3D graphics engine and performs the simulation via a VR / AR device.

[0440] Step 6:

[0441] The server allows external engineers to add functionality to the system through an open API. The input is a new external program, and the output is a system with extensions that integrate that program. Specifically, it processes API requests, stores the results in a database, and applies them to the entire system.

[0442] This series of steps enables the collection of community opinions in a readily accessible format in real time, and allows for sustainable urban planning based on data analysis.

[0443] (Application Example 1)

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

[0445] In urban planning aimed at the sustainable development of local communities, it is crucial to effectively collect and reflect the diverse opinions of residents. However, traditional systems have suffered from problems such as insufficient visibility of residents' proposals and difficulties in smooth communication between planners and residents. Furthermore, the lack of means to promote residents' intuitive understanding of new urban planning proposals has hindered the effective implementation of plans.

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

[0447] In this invention, the server includes a human interface means for collecting user opinions, an information processing means for analyzing the collected data and formulating urban plans, a display means for visualizing the analysis results and enabling simulation of user proposals in a virtual environment, and a means for providing visual feedback on the plan using augmented reality technology. This makes it possible to intuitively understand residents' proposals and to communicate smoothly with planners.

[0448] "Human interface means for collecting opinions" refers to communication technologies and devices for obtaining feedback and suggestions from users in real time.

[0449] "Information processing tools for analyzing data and formulating urban plans" refer to algorithms and computer programs that automatically generate plans for urban development and problem solving based on collected data.

[0450] "A display means that visualizes analysis results and enables user proposals to be simulated in a virtual environment" refers to a technological device that graphically represents the results of data analysis and enables users to test their proposed plans in a virtual environment.

[0451] "Means of providing visual feedback on plans using augmented reality technology" refers to devices or software that utilize augmented reality technology to visually present a proposed plan to the user in a way that overlays it onto the real world, thereby facilitating understanding.

[0452] "Development support tools" refer to technical foundations and platforms that enable multiple developers to collaborate in adding or improving new features to a system.

[0453] The system for implementing this invention has the following configuration in order to contribute to the sustainable development of the local community.

[0454] The server leverages a cloud computing platform with advanced data analysis capabilities to collect user feedback and perform real-time data processing for use in urban planning. To this end, it uses Google Cloud Platform's machine learning tools to collect diverse data from local governments and social media, storing it in Firebase. Machine learning algorithms are applied to the analysis, predicting regional demographics and economic trends. The analysis results are visualized on a dashboard and provided to users.

[0455] The terminal serves as an interface for residents to access the system and features a cross-platform application developed with React Native. Users can easily submit opinions and suggestions using this application. These opinions are sent to the server and used for analysis.

[0456] Furthermore, the Unity engine and AR Foundation will be used as simulation tools utilizing augmented reality technology. This will allow users to visualize their proposed urban plans in a virtual environment and intuitively verify them. For example, a user can submit a proposal for a new park and then view its completed image using AR.

[0457] As a concrete example, we can propose a design for a multi-purpose plaza where elderly people can gather in an aging community. An example of a prompt to input into the generating AI model would be, "I have submitted a design for a multi-purpose plaza for the elderly. I would like to check the completed image using AR."

[0458] In this way, the system can directly reflect residents' opinions in urban planning and promote communication between residents and planners.

[0459] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0460] Step 1:

[0461] Users input opinions and suggestions via a terminal. The input data is sent to the server through a human interface. Here, the input is the user's opinions and suggestions, and the output is data packets based on them that are sent to the server.

[0462] Step 2:

[0463] The server saves the received opinions and suggestions to Google Firebase. Here, the input is the data packet sent in step 1, and the output is the status of the data being saved to the database. The saved data is then subjected to subsequent analysis.

[0464] Step 3:

[0465] The server analyzes the stored data using machine learning tools on Google Cloud Platform. Here, the input consists of user opinions and city data stored in a database, and the output obtained from the analysis is predictions of demographic and economic trends. This analysis is performed by combining data processing and machine learning algorithms.

[0466] Step 4:

[0467] The server visualizes the analysis results on a dashboard and sends them to the terminal. The input is the analysis results, and the output is the visualized data. Through this data, the user can check the predicted results of the proposed urban plan.

[0468] Step 5:

[0469] Through an application on their device, users utilize the Unity engine and AR Foundation to run virtual simulations based on their proposals. The input consists of the user's proposal and visualization data, while the output is visual feedback in an AR environment. This process allows users to intuitively understand the feasibility and impact of their proposals.

[0470] 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.

[0471] This invention provides an urban planning system that considers not only the opinions of residents but also their emotional states. This enables a more sophisticated form of resident-participatory planning. The system consists of three elements: a server, terminals, and users, and their roles are interconnected.

[0472] The server first has the function of collecting data from local governments and social media, and this data is stored in a database. It also has an information processing system equipped with an emotion engine, which allows it to analyze the emotional state of users. The server uses this emotion data to supplement the information on the background in which residents' opinions were submitted and to perform a more detailed analysis.

[0473] The terminal provides a means for residents to input opinions and suggestions through a user interface. In addition, the terminal works in conjunction with an emotion engine to collect emotional data expressed by users during their interaction with the interface. This emotional data is immediately transmitted to a server and recorded in a database.

[0474] The server analyzes emotional data during the information processing process and generates urban planning proposals that take this into account. The analysis results are displayed on a dashboard and provided in a visually easy-to-understand format for users. By analyzing emotional data, it is also possible to pre-evaluate the level of public acceptance of the plan.

[0475] Furthermore, the device is equipped with display methods that utilize virtual reality and augmented reality. Users can experience the proposed plan in a virtual environment, and the emotional changes they experience are analyzed again by an emotion engine and sent to the server as immediate feedback. This allows for real-time adjustments to the urban plan.

[0476] As a concrete example of considering emotions, in a new park design plan, the server analyzes emotional data such as residents' expectations and concerns about the plan, along with their opinions. If a user feels enjoyment or reassurance during a simulation experience using a terminal, the direction of the plan can be fine-tuned accordingly.

[0477] Thus, this invention enables advanced opinion gathering and analysis using an emotion engine, allowing for the formulation of urban plans that more accurately reflect the intentions of residents. This contributes to the sustainable development of local communities.

[0478] The following describes the processing flow.

[0479] Step 1:

[0480] The server collects demographic data and resident opinion submission data through open data from local governments and social media APIs, and stores it in a database. At this time, the data is organized in an appropriate format to prepare it for subsequent processing.

[0481] Step 2:

[0482] The terminal receives opinions and suggestions from residents through its user interface. When a user inputs information, the terminal's built-in emotion engine acquires emotional data from the user's facial expressions and voice.

[0483] Step 3:

[0484] Users input their opinions and suggestions through their devices and add comments as needed. This information, along with sentiment data collected by the sentiment engine, is immediately sent to the server.

[0485] Step 4:

[0486] The server analyzes the received user opinions and sentiment data using information processing tools. By analyzing sentiment trends, it understands the emotional responses behind residents' opinions and uses this information in urban planning. The analysis results are visualized on a dashboard and made available to stakeholders.

[0487] Step 5:

[0488] The device provides a simulation environment that allows users to experience urban planning proposals using virtual reality or augmented reality technology. Users can experience the plan within this virtual environment and resubmit their feedback based on the visualized results.

[0489] Step 6:

[0490] The emotional changes the user exhibits during the experience are again collected by the device's emotion engine. This feedback data is also sent to the server and analyzed immediately.

[0491] Step 7:

[0492] The server uses newly acquired emotional feedback to identify areas for adjustment and improvement in the plan. It generates an optimized plan that reflects the user's emotions and notifies stakeholders of the update via the dashboard.

[0493] Step 8:

[0494] The server provides analytical data to external developers via open APIs, supporting the development of new features and improvement tools. This provision allows various solutions to be applied to address region-specific challenges.

[0495] (Example 2)

[0496] 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."

[0497] Modern urban planning requires not only gathering user opinions but also conducting analyses from diverse perspectives that take emotions into account. However, conventional systems have struggled to efficiently analyze emotional states and reflect them in planning in real time. Therefore, there is a need for efficient methods to quickly and accurately formulate beneficial urban plans.

[0498] 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.

[0499] In this invention, the server includes a human interface means for collecting user opinions and emotional states, an information processing means for analyzing the collected data and formulating urban plans using a generative AI model, and a display means for visualizing the plan proposal based on the analyzed opinion and emotional data and enabling simulation in a virtual environment. This makes it possible to formulate sophisticated and intuitive urban plans that include emotions.

[0500] "Human interface means" refers to devices or software for users to input their opinions and emotional states, and the data collected through these means forms the basis for analysis.

[0501] "Information processing means" refers to systems and algorithms that analyze collected opinion and sentiment data and use generative AI models to formulate urban plans.

[0502] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to predict and generate optimal urban planning proposals from opinion and sentiment data.

[0503] "Display means" refers to a device or computer program that visualizes analysis and simulation results and helps users easily understand them, and may utilize virtual reality or augmented reality technologies.

[0504] A "virtual environment" refers to a computer-generated environment used to visually simulate a plan, allowing users to experience situations and spaces that do not actually exist.

[0505] "Data communication methods" refer to infrastructure and protocols used to transmit collected opinion and sentiment data to servers in real time for use in coordinating urban planning.

[0506] This invention provides a system that comprehensively handles everything from opinion gathering and analysis to simulation in a virtual environment, in order to formulate sophisticated and rapid urban plans. This system mainly consists of servers, terminals, and users, each of which works in conjunction with the others.

[0507] The server first collects opinions and comments from local governments and online social platforms via APIs. Common web scraping tools and API clients are used for this data collection. Next, the server organizes and stores the collected data in a database. General SQL database management systems and NoSQL databases are suitable for database management.

[0508] The server uses a generative AI model to analyze the collected data. This generative AI model extracts emotional data from opinions and incorporates it into urban planning proposals. Natural language processing techniques are employed in this analysis, specifically an AI algorithm implemented to identify emotions from text.

[0509] The terminal provides an interface for users to input their opinions and simultaneously collects emotional data expressed during the input process. At this stage, real-time data transmission and secure communication protocols are crucial, and technologies such as WebSocket are used.

[0510] Furthermore, the device provides users with a means to visualize urban planning proposals using virtual reality (VR) and augmented reality (AR). This allows users to experience a virtual environment of the plan and provide specific feedback. Technologies supporting this process include VR / AR platforms, such as engines like Unity.

[0511] Through their experience in a virtual environment, users provide emotional feedback to the proposed plan via their devices, sending it back to the server. This allows the urban planning proposal to be adjusted in real time, more accurately reflecting the intentions of the residents.

[0512] An example of this system's use is a design plan for a new park. The server analyzes residents' opinions and feelings about the plan and adjusts its direction based on indicators of safety and enjoyment. An example of a prompt might be, "Please tell me how to analyze residents' expectations and concerns regarding the design of the new park and adjust the direction of the plan."

[0513] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0514] Step 1:

[0515] The server collects opinion data through municipal databases and online platform APIs. This input data consists of opinions and comments in text format, which the server stores in its database. Specific scraping tools and API clients are used for data collection. For example, text data is input, and structured data is stored in the database as a result.

[0516] Step 2:

[0517] The server analyzes the collected opinion data using a generative AI model. The structured data saved in step 1 is taken in as input. The server uses the generative AI model to detect and classify emotions in the data and generate insights that can be used in urban planning. As a result, new analyzed emotion data is obtained.

[0518] Step 3:

[0519] The terminal receives opinions and emotional states directly from the user as input through a human interface. At this time, the terminal collects data in real time through the user interface and transmits it to the server. Real-time input data includes the user's opinions and intuitive feedback. The output is raw data that is immediately transmitted to the server.

[0520] Step 4:

[0521] The server re-analyzes the real-time sentiment data collected in step 3. This input data includes immediate feedback from users. The server integrates this real-time data into the existing plan and adjusts the urban planning proposal. As a result, a new urban planning proposal that reflects the users' sentiment data is output.

[0522] Step 5:

[0523] The terminal uses virtual reality and augmented reality technologies to present the generated urban planning proposal to the user. The input is the urban planning proposal generated in step 4. The terminal visually simulates the proposal and sets it up so that the user can experience a concrete space and situation. As a result, a visually represented proposal is provided to the user.

[0524] Step 6:

[0525] Users provide feedback based on their experiences in the virtual environment. Input includes judgments and emotions based on the user's experience. The terminal then sends this feedback back to the server, which is used to further refine the urban plan. Output is the transmission of user feedback data to the server.

[0526] (Application Example 2)

[0527] 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."

[0528] While resident participation is crucial in urban development planning, traditional methods often fail to adequately reflect residents' opinions and feelings, impacting the success or failure of the plan. Furthermore, real-time collection of opinions and understanding emotional states are difficult, hindering flexible adjustments to the plan.

[0529] 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.

[0530] In this invention, the server includes a user interface means for collecting user opinions and behavioral states, a data processing means for integrating the collected data and analyzed behavioral data to formulate a settlement plan, a visualization means for visualizing the analysis results and enabling a behavioral prediction experience in a virtual environment, and an open-source means for enabling collaboration with multiple participants. This makes it possible to collect residents' opinions and feelings in real time and formulate flexible urban plans that reflect them in the plan.

[0531] "User interface means" refers to input devices or software used to collect data on opinions and behavioral states from users.

[0532] "Data processing means" refers to an information processing device or software used to analyze and integrate collected opinion data and behavioral data in order to formulate a community plan.

[0533] "Visualization means" refers to a display device or software that visually displays the analyzed data results and allows users to experience behavioral prediction in a virtual environment.

[0534] "Open source methods" refer to techniques that involve releasing source code and APIs in order to expand and improve a system through collaboration among multiple participants and developers.

[0535] To implement this invention, a system is constructed in which a server, a terminal, and a user cooperate. The server collects user opinions and behavioral states in real time and analyzes them using data processing means. Specifically, the "TextBlob" library in Python is used to perform text analysis on emotional data, and software such as "Unity" and "ARKit / ARCore" are used for the virtual reality experience.

[0536] The terminal is envisioned as hardware such as smartphones and tablets, and is equipped with a user interface. Here, an application is implemented that allows residents to input their opinions, and is configured to collect their emotional states at the same time. Furthermore, as a means of visualization, users are provided with a virtual community planning experience, enabling them to predict their own behavior.

[0537] Users experience the visualized plan in virtual reality via an application on their device. The opinions and emotional states gained through this experience are shared with other participants through open-source means and used to improve the plan.

[0538] One concrete example is a residential area improvement plan, where users can virtually walk around the area through the app and send their impressions and opinions in real time. An example of a prompt message would be, "Please tell us in detail what you felt and where you felt after experiencing the new park design plan in virtual reality."

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

[0540] Step 1:

[0541] The device receives input from the user regarding opinions and emotional states via a user interface. This input includes opinions in text format and emotional state data obtained from sensors. The device temporarily stores this data and sends it to the server.

[0542] Step 2:

[0543] The server analyzes opinion and emotional state data received from the terminal. Here, the Python library "TextBlob" is used for text sentiment analysis. The input opinion data is classified into emotional categories such as positive, negative, and neutral. These results are stored in a database.

[0544] Step 3:

[0545] The server uses data processing tools to formulate a settlement plan. It incorporates previously analyzed opinion and sentiment data and uses a generative AI model to analyze the overall residents' evaluation. This results in the output of a plan that reflects the residents' opinions and sentiments.

[0546] Step 4:

[0547] The server uses visualization tools to visualize the drafted plan. To provide a virtual reality experience, it utilizes Unity and ARKit / ARCore to generate a three-dimensional environment. This environment data is then sent back to the terminal.

[0548] Step 5:

[0549] Users experience a settlement plan generated in virtual reality using their device. During this experience, users can input new opinions, and their emotional state is continuously detected by sensors and immediately sent back to the server. This process enables real-time adjustment of the plan.

[0550] 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.

[0551] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0552] 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.

[0553] [Fourth Embodiment]

[0554] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0555] 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.

[0556] 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).

[0557] 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.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] 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.

[0565] 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.

[0566] 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".

[0567] This invention is a system for collecting residents' opinions and incorporating them into urban planning in order to support the sustainable development of local communities. The system operates primarily around three elements: a server, terminals, and users, and aims to improve the efficiency of urban planning through effective cooperation between them.

[0568] The server uses a data collection module to gather diverse data from local governments and social media in real time and store it in a dedicated database. This data includes multifaceted information such as local demographics and the latest opinions of residents.

[0569] Furthermore, the server uses advanced information processing tools to analyze the collected data. Using sophisticated machine learning algorithms, it predicts population growth and decline, as well as economic trends. The results of this analysis are visualized on a dashboard and provided to terminal users via their devices.

[0570] The terminal functions as an interface between residents and the local government, providing a user interface for residents to access. Through this interface, users can submit their opinions and proposed plans. These opinions are sent to the server and incorporated into the analysis.

[0571] The terminal also features display methods that utilize virtual environments and augmented reality technology. This allows users to visually confirm simulations based on their proposals and intuitively understand the impact of their plans.

[0572] Furthermore, the server provides an open API, allowing external developers to add new functionality to the system. The open API facilitates smooth data exchange between the server and external programs. This creates an environment where residents, local businesses, and universities can collaborate to develop solutions that address region-specific challenges.

[0573] As a concrete example, in areas with an aging population, a server identifies the increasing trend of elderly people through data analysis. Using terminals, feedback is received from residents, and simulations are conducted to improve the design of public facilities based on that feedback. As a result, efficient and livable urban design becomes possible.

[0574] This invention aims to realize flexible and sustainable urban planning by incorporating a community-based, resident-participatory approach into the system.

[0575] The following describes the processing flow.

[0576] Step 1:

[0577] The server collects demographic and environmental data from open data sources provided by local governments and stores it in a database. It also obtains residents' opinions and trend data in real time through social media APIs.

[0578] Step 2:

[0579] The server cleanses the collected data, removing unnecessary data and imputing missing values. The data is then formatted to a format suitable for analysis.

[0580] Step 3:

[0581] The server uses machine learning algorithms to predict demographic and economic trends and generate analysis results. This allows for the evaluation of future changes and their incorporation into planning.

[0582] Step 4:

[0583] The terminal provides a user interface for resident participation. Through this interface, users can input suggestions and opinions regarding urban planning.

[0584] Step 5:

[0585] The server receives opinion data from residents and incorporates it as part of the data analysis. The analysis results, which take residents' opinions into account, are displayed on a dashboard.

[0586] Step 6:

[0587] The device runs simulations using VR or AR technology, allowing users to experience proposed urban planning changes in a virtual space. Through this experience, users can participate in optimizing the plan.

[0588] Step 7:

[0589] The server provides data access to external developers through open APIs, supporting the development of additional features and new tools. This facilitates the development of region-specific solutions.

[0590] (Example 1)

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

[0592] Modern urban planning not only struggles to adequately reflect the opinions of local communities, but also requires rapid responses to predicted demographic changes and technological advancements. However, traditional methods struggle with rapid and accurate data collection and analysis, and the environment for diverse stakeholders to collaborate and expand functionality is not adequately developed. New tools are needed to improve this situation and realize sustainable urban planning.

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

[0594] In this invention, the server includes data processing means for collecting and analyzing data, a display device for visualizing the analyzed information and enabling simulations in a virtual space, and a public API means for enabling collaboration with multiple engineers. This makes it possible to collect opinions from local residents in real time, predict demographic changes, and conduct planning simulations in a virtual space, while developing sustainable urban plans optimized for the region through collaboration with diverse stakeholders.

[0595] A "human interface means" is a means by which users input opinions into a system and obtain information.

[0596] "Data processing means" refers to means for analyzing collected data and extracting relevant information.

[0597] A "display device" is a means of visualizing analyzed information in the form of graphics or videos and presenting it in a way that is easy for users to understand.

[0598] A "public API means" is a means of providing an interface that allows external engineers to add new functions to a system or utilize existing data.

[0599] A "machine learning algorithm" is an algorithm that learns patterns and trends from large amounts of data to predict future population trends and economic conditions.

[0600] "External platform integration means" refers to means for exchanging data with other systems and applications and extending their functionality.

[0601] This invention is an urban planning system designed to support the sustainable development of local communities. The system primarily consists of three elements: a server, terminals, and users.

[0602] The server utilizes a data collection module to collect data in real time from local governments and online platforms. The data is automatically recorded in a dedicated database via an API over the internet. The collected information includes residents' opinions, demographic trends, and economic indicators. The server then analyzes the data using machine learning algorithms written in programming languages ​​such as Python and R. This makes it possible to predict future population trends and socioeconomic trends. The analysis results are displayed on a dashboard using visualization tools and sent to the user's device.

[0603] The terminal functions as an interface with residents and local government officials. Users can directly input their opinions and suggestions using the interface provided on the terminal. This information is sent to a server and used for analysis. The terminal also features display functions using virtual reality (VR) and augmented reality (AR) technologies. This allows for the visual presentation of simulations based on suggestions, and users can see the impact in real time. For example, by using a VR headset or an AR application on a smartphone, users can experience future urban design.

[0604] Users can submit opinions to the system via their devices and receive feedback. This enables community-participatory urban planning. Users can also view the provided simulations, develop new proposals, and input them back into the system. This process allows for flexible urban planning based on the diverse needs of the community.

[0605] As a concrete example, in areas with an aging population, a server performs data analysis to identify an increasing trend in residents aged 60 and over. Opinions on improving access to public facilities are collected from residents via terminals, and simulations based on these opinions are provided on the terminals. This allows residents to virtually try out the improvement proposals they have made. An example of a prompt for the generated AI model is, "Please create a proposal for sustainable urban planning based on local demographics and residents' opinions. Please include ideas for design improvements to public facilities in areas with an aging population."

[0606] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0607] Step 1:

[0608] The server collects data from local governments and online platforms via APIs. The data received as input includes residents' opinions, local demographics, and economic activity information. Storing this data in a dedicated database enables real-time information updates. Specifically, a program operates that periodically collects publicly available data from local governments and feeds from social media via a network connection.

[0609] Step 2:

[0610] The server inputs the collected data into a machine learning algorithm for analysis. This process classifies and aggregates the information to predict demographic trends and identify trends in economic activity. The output includes predictions of future trends and regional opinion tendencies. Specifically, statistical analysis libraries such as Python are used to train and infer the model.

[0611] Step 3:

[0612] The server visualizes the analysis results in a dashboard format and sends them to the terminal. The input is the analyzed data, and the output is visualized graphs and charts. Specifically, it uses data visualization tools to graphically transform the data and delivers it to the terminal via a web interface.

[0613] Step 4:

[0614] The terminal displays visualized data in a user interface. Users view this, intuitively understand the information, and input their own opinions. In this step, resident feedback is added as user input, which is then incorporated into the next data collection cycle. Specifically, the terminal accepts user input via a touchscreen or keyboard and sends it to a server.

[0615] Step 5:

[0616] The device uses virtual and augmented reality to provide a simulation of urban planning based on user proposals. The input is the user's proposal, and the output is a simulated urban environment. Specifically, the device generates a virtual model using a 3D graphics engine and performs the simulation via a VR / AR device.

[0617] Step 6:

[0618] The server allows external engineers to add functionality to the system through an open API. The input is a new external program, and the output is a system with extensions that integrate that program. Specifically, it processes API requests, stores the results in a database, and applies them to the entire system.

[0619] This series of steps enables the collection of community opinions in a readily accessible format in real time, and allows for sustainable urban planning based on data analysis.

[0620] (Application Example 1)

[0621] 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".

[0622] In urban planning aimed at the sustainable development of local communities, it is crucial to effectively collect and reflect the diverse opinions of residents. However, traditional systems have suffered from problems such as insufficient visibility of residents' proposals and difficulties in smooth communication between planners and residents. Furthermore, the lack of means to promote residents' intuitive understanding of new urban planning proposals has hindered the effective implementation of plans.

[0623] 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.

[0624] In this invention, the server includes a human interface means for collecting user opinions, an information processing means for analyzing the collected data and formulating urban plans, a display means for visualizing the analysis results and enabling simulation of user proposals in a virtual environment, and a means for providing visual feedback on the plan using augmented reality technology. This makes it possible to intuitively understand residents' proposals and to communicate smoothly with planners.

[0625] "Human interface means for collecting opinions" refers to communication technologies and devices for obtaining feedback and suggestions from users in real time.

[0626] "Information processing tools for analyzing data and formulating urban plans" refer to algorithms and computer programs that automatically generate plans for urban development and problem solving based on collected data.

[0627] "A display means that visualizes analysis results and enables user proposals to be simulated in a virtual environment" refers to a technological device that graphically represents the results of data analysis and enables users to test their proposed plans in a virtual environment.

[0628] "Means of providing visual feedback on plans using augmented reality technology" refers to devices or software that utilize augmented reality technology to visually present a proposed plan to the user in a way that overlays it onto the real world, thereby facilitating understanding.

[0629] "Development support tools" refer to technical foundations and platforms that enable multiple developers to collaborate in adding or improving new features to a system.

[0630] The system for implementing this invention has the following configuration in order to contribute to the sustainable development of the local community.

[0631] The server leverages a cloud computing platform with advanced data analysis capabilities to collect user feedback and perform real-time data processing for use in urban planning. To this end, it uses Google Cloud Platform's machine learning tools to collect diverse data from local governments and social media, storing it in Firebase. Machine learning algorithms are applied to the analysis, predicting regional demographics and economic trends. The analysis results are visualized on a dashboard and provided to users.

[0632] The terminal serves as an interface for residents to access the system and features a cross-platform application developed with React Native. Users can easily submit opinions and suggestions using this application. These opinions are sent to the server and used for analysis.

[0633] Furthermore, the Unity engine and AR Foundation will be used as simulation tools utilizing augmented reality technology. This will allow users to visualize their proposed urban plans in a virtual environment and intuitively verify them. For example, a user can submit a proposal for a new park and then view its completed image using AR.

[0634] As a concrete example, we can propose a design for a multi-purpose plaza where elderly people can gather in an aging community. An example of a prompt to input into the generating AI model would be, "I have submitted a design for a multi-purpose plaza for the elderly. I would like to check the completed image using AR."

[0635] In this way, the system can directly reflect residents' opinions in urban planning and promote communication between residents and planners.

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

[0637] Step 1:

[0638] Users input opinions and suggestions via a terminal. The input data is sent to the server through a human interface. Here, the input is the user's opinions and suggestions, and the output is data packets based on them that are sent to the server.

[0639] Step 2:

[0640] The server saves the received opinions and suggestions to Google Firebase. Here, the input is the data packet sent in step 1, and the output is the status of the data being saved to the database. The saved data is then subjected to subsequent analysis.

[0641] Step 3:

[0642] The server analyzes the stored data using machine learning tools on Google Cloud Platform. Here, the input consists of user opinions and city data stored in a database, and the output obtained from the analysis is predictions of demographic and economic trends. This analysis is performed by combining data processing and machine learning algorithms.

[0643] Step 4:

[0644] The server visualizes the analysis results on a dashboard and sends them to the terminal. The input is the analysis results, and the output is the visualized data. Through this data, the user can check the predicted results of the proposed urban plan.

[0645] Step 5:

[0646] Through an application on their device, users utilize the Unity engine and AR Foundation to run virtual simulations based on their proposals. The input consists of the user's proposal and visualization data, while the output is visual feedback in an AR environment. This process allows users to intuitively understand the feasibility and impact of their proposals.

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

[0648] This invention provides an urban planning system that considers not only the opinions of residents but also their emotional states. This enables a more sophisticated form of resident-participatory planning. The system consists of three elements: a server, terminals, and users, and their roles are interconnected.

[0649] The server first has the function of collecting data from local governments and social media, and this data is stored in a database. It also has an information processing system equipped with an emotion engine, which allows it to analyze the emotional state of users. The server uses this emotion data to supplement the information on the background in which residents' opinions were submitted and to perform a more detailed analysis.

[0650] The terminal provides a means for residents to input opinions and suggestions through a user interface. In addition, the terminal works in conjunction with an emotion engine to collect emotional data expressed by users during their interaction with the interface. This emotional data is immediately transmitted to a server and recorded in a database.

[0651] The server analyzes emotional data during the information processing process and generates urban planning proposals that take this into account. The analysis results are displayed on a dashboard and provided in a visually easy-to-understand format for users. By analyzing emotional data, it is also possible to pre-evaluate the level of public acceptance of the plan.

[0652] Furthermore, the device is equipped with display methods that utilize virtual reality and augmented reality. Users can experience the proposed plan in a virtual environment, and the emotional changes they experience are analyzed again by an emotion engine and sent to the server as immediate feedback. This allows for real-time adjustments to the urban plan.

[0653] As a concrete example of considering emotions, in a new park design plan, the server analyzes emotional data such as residents' expectations and concerns about the plan, along with their opinions. If a user feels enjoyment or reassurance during a simulation experience using a terminal, the direction of the plan can be fine-tuned accordingly.

[0654] Thus, this invention enables advanced opinion gathering and analysis using an emotion engine, allowing for the formulation of urban plans that more accurately reflect the intentions of residents. This contributes to the sustainable development of local communities.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] The server collects demographic data and resident opinion submission data through open data from local governments and social media APIs, and stores it in a database. At this time, the data is organized in an appropriate format to prepare it for subsequent processing.

[0658] Step 2:

[0659] The terminal receives opinions and suggestions from residents through its user interface. When a user inputs information, the terminal's built-in emotion engine acquires emotional data from the user's facial expressions and voice.

[0660] Step 3:

[0661] Users input their opinions and suggestions through their devices and add comments as needed. This information, along with sentiment data collected by the sentiment engine, is immediately sent to the server.

[0662] Step 4:

[0663] The server analyzes the received user opinions and sentiment data using information processing tools. By analyzing sentiment trends, it understands the emotional responses behind residents' opinions and uses this information in urban planning. The analysis results are visualized on a dashboard and made available to stakeholders.

[0664] Step 5:

[0665] The device provides a simulation environment that allows users to experience urban planning proposals using virtual reality or augmented reality technology. Users can experience the plan within this virtual environment and resubmit their feedback based on the visualized results.

[0666] Step 6:

[0667] The emotional changes the user exhibits during the experience are again collected by the device's emotion engine. This feedback data is also sent to the server and analyzed immediately.

[0668] Step 7:

[0669] The server uses newly acquired emotional feedback to identify areas for adjustment and improvement in the plan. It generates an optimized plan that reflects the user's emotions and notifies stakeholders of the update via the dashboard.

[0670] Step 8:

[0671] The server provides analytical data to external developers via open APIs, supporting the development of new features and improvement tools. This provision allows various solutions to be applied to address region-specific challenges.

[0672] (Example 2)

[0673] 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".

[0674] Modern urban planning requires not only gathering user opinions but also conducting analyses from diverse perspectives that take emotions into account. However, conventional systems have struggled to efficiently analyze emotional states and reflect them in planning in real time. Therefore, there is a need for efficient methods to quickly and accurately formulate beneficial urban plans.

[0675] 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.

[0676] In this invention, the server includes a human interface means for collecting user opinions and emotional states, an information processing means for analyzing the collected data and formulating urban plans using a generative AI model, and a display means for visualizing the plan proposal based on the analyzed opinion and emotional data and enabling simulation in a virtual environment. This makes it possible to formulate sophisticated and intuitive urban plans that include emotions.

[0677] "Human interface means" refers to devices or software for users to input their opinions and emotional states, and the data collected through these means forms the basis for analysis.

[0678] "Information processing means" refers to systems and algorithms that analyze collected opinion and sentiment data and use generative AI models to formulate urban plans.

[0679] A "generative AI model" refers to an algorithm or program that uses artificial intelligence technology to predict and generate optimal urban planning proposals from opinion and sentiment data.

[0680] "Display means" refers to a device or computer program that visualizes analysis and simulation results and helps users easily understand them, and may utilize virtual reality or augmented reality technologies.

[0681] A "virtual environment" refers to a computer-generated environment used to visually simulate a plan, allowing users to experience situations and spaces that do not actually exist.

[0682] "Data communication methods" refer to infrastructure and protocols used to transmit collected opinion and sentiment data to servers in real time for use in coordinating urban planning.

[0683] This invention provides a system that comprehensively handles everything from opinion gathering and analysis to simulation in a virtual environment, in order to formulate sophisticated and rapid urban plans. This system mainly consists of servers, terminals, and users, each of which works in conjunction with the others.

[0684] The server first collects opinions and comments from local governments and online social platforms via APIs. Common web scraping tools and API clients are used for this data collection. Next, the server organizes and stores the collected data in a database. General SQL database management systems and NoSQL databases are suitable for database management.

[0685] The server uses a generative AI model to analyze the collected data. This generative AI model extracts emotional data from opinions and incorporates it into urban planning proposals. Natural language processing techniques are employed in this analysis, specifically an AI algorithm implemented to identify emotions from text.

[0686] The terminal provides an interface for users to input their opinions and simultaneously collects emotional data expressed during the input process. At this stage, real-time data transmission and secure communication protocols are crucial, and technologies such as WebSocket are used.

[0687] Furthermore, the device provides users with a means to visualize urban planning proposals using virtual reality (VR) and augmented reality (AR). This allows users to experience a virtual environment of the plan and provide specific feedback. Technologies supporting this process include VR / AR platforms, such as engines like Unity.

[0688] Through their experience in a virtual environment, users provide emotional feedback to the proposed plan via their devices, sending it back to the server. This allows the urban planning proposal to be adjusted in real time, more accurately reflecting the intentions of the residents.

[0689] An example of this system's use is a design plan for a new park. The server analyzes residents' opinions and feelings about the plan and adjusts its direction based on indicators of safety and enjoyment. An example of a prompt might be, "Please tell me how to analyze residents' expectations and concerns regarding the design of the new park and adjust the direction of the plan."

[0690] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0691] Step 1:

[0692] The server collects opinion data through municipal databases and online platform APIs. This input data consists of opinions and comments in text format, which the server stores in its database. Specific scraping tools and API clients are used for data collection. For example, text data is input, and structured data is stored in the database as a result.

[0693] Step 2:

[0694] The server analyzes the collected opinion data using a generative AI model. The structured data saved in step 1 is taken in as input. The server uses the generative AI model to detect and classify emotions in the data and generate insights that can be used in urban planning. As a result, new analyzed emotion data is obtained.

[0695] Step 3:

[0696] The terminal receives opinions and emotional states directly from the user as input through a human interface. At this time, the terminal collects data in real time through the user interface and transmits it to the server. Real-time input data includes the user's opinions and intuitive feedback. The output is raw data that is immediately transmitted to the server.

[0697] Step 4:

[0698] The server re-analyzes the real-time sentiment data collected in step 3. This input data includes immediate feedback from users. The server integrates this real-time data into the existing plan and adjusts the urban planning proposal. As a result, a new urban planning proposal that reflects the users' sentiment data is output.

[0699] Step 5:

[0700] The terminal uses virtual reality and augmented reality technologies to present the generated urban planning proposal to the user. The input is the urban planning proposal generated in step 4. The terminal visually simulates the proposal and sets it up so that the user can experience a concrete space and situation. As a result, a visually represented proposal is provided to the user.

[0701] Step 6:

[0702] Users provide feedback based on their experiences in the virtual environment. Input includes judgments and emotions based on the user's experience. The terminal then sends this feedback back to the server, which is used to further refine the urban plan. Output is the transmission of user feedback data to the server.

[0703] (Application Example 2)

[0704] 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".

[0705] While resident participation is crucial in urban development planning, traditional methods often fail to adequately reflect residents' opinions and feelings, impacting the success or failure of the plan. Furthermore, real-time collection of opinions and understanding emotional states are difficult, hindering flexible adjustments to the plan.

[0706] 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.

[0707] In this invention, the server includes a user interface means for collecting user opinions and behavioral states, a data processing means for integrating the collected data and analyzed behavioral data to formulate a settlement plan, a visualization means for visualizing the analysis results and enabling a behavioral prediction experience in a virtual environment, and an open-source means for enabling collaboration with multiple participants. This makes it possible to collect residents' opinions and feelings in real time and formulate flexible urban plans that reflect them in the plan.

[0708] "User interface means" refers to input devices or software used to collect data on opinions and behavioral states from users.

[0709] "Data processing means" refers to an information processing device or software used to analyze and integrate collected opinion data and behavioral data in order to formulate a community plan.

[0710] "Visualization means" refers to a display device or software that visually displays the analyzed data results and allows users to experience behavioral prediction in a virtual environment.

[0711] "Open source methods" refer to techniques that involve releasing source code and APIs in order to expand and improve a system through collaboration among multiple participants and developers.

[0712] To implement this invention, a system is constructed in which a server, a terminal, and a user cooperate. The server collects user opinions and behavioral states in real time and analyzes them using data processing means. Specifically, the "TextBlob" library in Python is used to perform text analysis on emotional data, and software such as "Unity" and "ARKit / ARCore" are used for the virtual reality experience.

[0713] The terminal is envisioned as hardware such as smartphones and tablets, and is equipped with a user interface. Here, an application is implemented that allows residents to input their opinions, and is configured to collect their emotional states at the same time. Furthermore, as a means of visualization, users are provided with a virtual community planning experience, enabling them to predict their own behavior.

[0714] Users experience the visualized plan in virtual reality via an application on their device. The opinions and emotional states gained through this experience are shared with other participants through open-source means and used to improve the plan.

[0715] One concrete example is a residential area improvement plan, where users can virtually walk around the area through the app and send their impressions and opinions in real time. An example of a prompt message would be, "Please tell us in detail what you felt and where you felt after experiencing the new park design plan in virtual reality."

[0716] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0717] Step 1:

[0718] The device receives input from the user regarding opinions and emotional states via a user interface. This input includes opinions in text format and emotional state data obtained from sensors. The device temporarily stores this data and sends it to the server.

[0719] Step 2:

[0720] The server analyzes opinion and emotional state data received from the terminal. Here, the Python library "TextBlob" is used for text sentiment analysis. The input opinion data is classified into emotional categories such as positive, negative, and neutral. These results are stored in a database.

[0721] Step 3:

[0722] The server uses data processing tools to formulate a settlement plan. It incorporates previously analyzed opinion and sentiment data and uses a generative AI model to analyze the overall residents' evaluation. This results in the output of a plan that reflects the residents' opinions and sentiments.

[0723] Step 4:

[0724] The server uses visualization tools to visualize the drafted plan. To provide a virtual reality experience, it utilizes Unity and ARKit / ARCore to generate a three-dimensional environment. This environment data is then sent back to the terminal.

[0725] Step 5:

[0726] Users experience a settlement plan generated in virtual reality using their device. During this experience, users can input new opinions, and their emotional state is continuously detected by sensors and immediately sent back to the server. This process enables real-time adjustment of the plan.

[0727] 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.

[0728] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0729] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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."

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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.

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] The following is further disclosed regarding the embodiments described above.

[0749] (Claim 1)

[0750] A human interface means for collecting user opinions,

[0751] Information processing tools for analyzing collected data and formulating urban plans,

[0752] A display means that visualizes the analysis results and enables simulation in a virtual environment,

[0753] An open API means that enables collaboration with multiple developers,

[0754] A system that includes this.

[0755] (Claim 2)

[0756] The system according to claim 1, characterized in that it collects opinions in real time using a human interface means.

[0757] (Claim 3)

[0758] The system according to claim 1, characterized in that the display means uses virtual reality or augmented reality.

[0759] "Example 1"

[0760] (Claim 1)

[0761] A human interface means for collecting user opinions,

[0762] A data processing means for collecting and analyzing data,

[0763] A display device that visualizes the analyzed information and enables simulation in a virtual space,

[0764] A public API that enables collaboration among multiple engineers,

[0765] A method for predicting population dynamics using machine learning algorithms,

[0766] External platform integration means for extending functionality according to specific regional needs,

[0767] A system that includes this.

[0768] (Claim 2)

[0769] The system according to claim 1, characterized by real-time opinion gathering.

[0770] (Claim 3)

[0771] The system according to claim 1, characterized by using virtual reality or augmented reality technology.

[0772] "Application Example 1"

[0773] (Claim 1)

[0774] A human interface means for collecting user opinions,

[0775] Information processing tools for analyzing collected data and formulating urban plans,

[0776] A display means that visualizes the analysis results and enables the user's proposals to be simulated in a virtual environment,

[0777] Development support tools that enable collaboration with multiple developers,

[0778] A means of providing visual feedback on the plan using augmented reality technology,

[0779] A system that includes this.

[0780] (Claim 2)

[0781] The system according to claim 1, characterized in that it collects opinions in real time using an information terminal via a human interface means.

[0782] (Claim 3)

[0783] The system according to claim 1, characterized in that the display means uses augmented reality or virtual reality to provide a visual simulation of a city plan proposed by the user.

[0784] "Example 2 of combining an emotion engine"

[0785] (Claim 1)

[0786] A human interface means for collecting user opinions and emotional states,

[0787] Information processing means for analyzing collected data and formulating urban plans using a generated AI model,

[0788] A display means that visualizes the proposed plan based on analyzed opinion and sentiment data and enables simulation in a virtual environment,

[0789] A data communication method for receiving feedback from multiple users in real time and adjusting urban planning,

[0790] A system that includes this.

[0791] (Claim 2)

[0792] The system according to claim 1, characterized in that it collects opinions and emotional states in real time using a human interface means.

[0793] (Claim 3)

[0794] The system according to claim 1, characterized in that the display means feeds back the emotion analysis results using virtual reality or augmented reality.

[0795] "Application example 2 of combining emotional engines"

[0796] (Claim 1)

[0797] A user interface means for collecting user opinions and behavioral status,

[0798] A data processing system for integrating collected data and analyzed behavioral data to formulate community plans,

[0799] A visualization method that visualizes analysis results and enables a behavioral prediction experience in a virtual environment,

[0800] An open-source method that enables collaboration with multiple participants,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, characterized in that it collects opinions and emotional states in real time using a human interface means.

[0804] (Claim 3)

[0805] The system according to claim 1, characterized in that the display means uses a visual technology or augmentation technology that transcends dimensions. [Explanation of Symbols]

[0806] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A human interface means for collecting user opinions, Information processing tools for analyzing collected data and formulating urban plans, A display means that visualizes the analysis results and enables simulation in a virtual environment, An open API means that enables collaboration with multiple developers, A system that includes this.

2. The system according to claim 1, characterized in that it collects opinions in real time using a human interface means.

3. The system according to claim 1, characterized in that the display means uses virtual reality or augmented reality.

Images