system

Abstract

Provide a system. 【Solution means】 Data receiving means for obtaining information on the area and building provided by the user, Area analysis means for evaluating the current situation and characteristics of the target area based on the obtained data, Success case search means for extracting successful cases of effective redevelopment from around the world and finding similar examples according to the regional characteristics, Redevelopment proposal generation means for automatically generating a plurality of design plans for redevelopment based on the regional characteristics and successful cases, Financial effect prediction means for simulating the economic impact of the proposed redevelopment plan and predicting costs and benefits, Environmental impact assessment means for evaluating the potential impact of the redevelopment plan on the regional environment and considering sustainable design elements, Long-term impact assessment means for analyzing the long-term impact of the redevelopment plan on the regional society and economy and evaluating future development potential, A system including

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem that there is a lack of an efficient design process for realizing sustainable and highly economical redevelopment in depopulated areas and aging urban spaces. With the current method, it is difficult to quickly propose redevelopment that matches the regional characteristics, and planning considering environmental considerations and long-term impacts is also insufficient. As a result, the activation of the region and the reduction of the environmental load are not sufficiently achieved.

Means for Solving the Problems

[0005] This invention provides a system including data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means. This system generates an optimal redevelopment plan by rapidly analyzing regional characteristics and searching for success cases from around the world based on that analysis. It also provides a means to realize sustainable and economically advantageous urban redevelopment by predicting the economic effects and environmental impacts of redevelopment plans and evaluating their long-term impact on the region.

[0006] A "data receiving means" is a system component that acquires information about a region or building provided by the user.

[0007] A "regional analysis tool" is a system component that has the function of evaluating the current situation and characteristics of a target region based on acquired data.

[0008] A "success story search tool" is a system component that extracts effective redevelopment success stories from around the world and finds similar examples that are appropriate to the characteristics of each region.

[0009] The "redevelopment proposal generation method" is a system component that automatically generates multiple redevelopment design plans based on regional characteristics and successful case studies.

[0010] A "financial impact prediction tool" is a system component that simulates the economic impact of a proposed redevelopment plan and predicts costs and benefits.

[0011] An "environmental impact assessment tool" is a system component that evaluates the potential impact of a redevelopment plan on the local environment and considers sustainable design elements.

[0012] A "long-term impact assessment tool" is a system component that analyzes the long-term impact that a redevelopment plan will have on the local community and economy, and evaluates its potential for future development. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] 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.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means.

[0035] Regarding the data reception method, users input information about the target area and buildings using a terminal. This information includes, for example, location, population dynamics, and the current status of the facilities. The terminal then compiles this information and sends it to the server.

[0036] In regional analysis, the server uses the received data to analyze the current state of the region. By referring to historical databases, it extracts indicators related to population trends and economic activity, and identifies current problems.

[0037] The success story search mechanism uses a generator AI model to search for successful redevelopment cases around the world. It filters cases similar to regional characteristics and challenges, and provides the relevant data to the user's terminal.

[0038] The redevelopment proposal generation system uses a server to generate an optimal redevelopment plan based on regional characteristics and successful case studies. This proposal includes multiple design options that consider economic effects and residents' needs. The generated design options are visualized and sent to the user's terminal.

[0039] In the financial impact prediction method, the server simulates the economic effects of the proposed redevelopment plan. This includes calculating development costs and expected profits, as well as conducting a risk analysis.

[0040] In environmental impact assessments, the server evaluates the environmental impact of the proposed redevelopment plan. Environmental considerations are taken into account, and sustainable design elements are integrated.

[0041] Long-term impact assessment methods evaluate the long-term effects that servers have on local communities and economies. This involves analyzing the quality of life of residents and the potential for regional revitalization, and considering factors that contribute to future development.

[0042] As an example of this system, consider the process of redeveloping a shopping street in a regional city. When a user inputs location data and current conditions of the shopping street, the server identifies the depopulation problem and provides similar successful case studies. Next, it generates multiple redevelopment plans suitable for the shopping street and visualizes designs tailored to the needs of shops and residents. Furthermore, it simulates the economic effects of each proposal and suggests environmentally conscious designs. Through this process, users can select the appropriate redevelopment plan for revitalizing the shopping street.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user inputs information about the target area or building into the device. This includes location information, current facility status, and demographic data.

[0046] Step 2:

[0047] The terminal processes the input information and sends it to the server as structured data. This involves data format conversion and transfer according to the necessary protocols.

[0048] Step 3:

[0049] The server analyzes the received data and uses regional analysis tools to assess the current situation. It compares this data with past data and cross-references it with databases to identify regional economic conditions and challenges faced by residents.

[0050] Step 4:

[0051] The server uses a generation AI model and a success story search method to find matching redevelopment cases around the world. It extracts similar projects and selects the case that is best suited to the regional characteristics.

[0052] Step 5:

[0053] The server uses a redevelopment proposal generation system to generate multiple redevelopment plans based on regional characteristics and successful case studies. These plans include design proposals that take into account the needs and economic benefits of the residents.

[0054] Step 6:

[0055] The server visualizes the generated proposals and sends them to the terminal. The terminal visually presents each project proposal so that the user can view and compare them.

[0056] Step 7:

[0057] The server uses financial effect prediction tools to simulate the economic impact of the redevelopment plan. For each proposed plan, it performs a cost analysis and calculates the expected profits.

[0058] Step 8:

[0059] The server uses environmental impact assessment tools to evaluate the environmental impact of each redevelopment plan. It verifies whether sustainable design elements are incorporated into the proposal and suggests improvements as needed.

[0060] Step 9:

[0061] The long-term impact of the server on local communities and economies will be evaluated using long-term impact assessment methods. The potential for improving the quality of life for local residents and stimulating the economy will be analyzed.

[0062] Step 10:

[0063] Users receive various reports via their devices and select the most suitable option from several proposed redevelopment plans. Through this process, effective redevelopment aimed at sustainable regional development is carried out.

[0064] (Example 1)

[0065] 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."

[0066] Redeveloping sparsely populated areas and dilapidated buildings presents challenges in formulating appropriate plans tailored to local characteristics. It requires ensuring economic and environmental sustainability while delivering long-term benefits to the local community. However, previous redevelopment projects have struggled to quickly process extensive data and conduct accurate analysis and evaluation, thus failing to derive optimal redevelopment strategies.

[0067] 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.

[0068] In this invention, the server includes means for inputting and transmitting data to the server, means for analyzing the current situation in the region, and means for searching for successful cases using an AI model. This makes it possible to quickly generate optimal redevelopment plans tailored to regional characteristics and provide sustainable redevelopment measures by conducting economic and environmental evaluations.

[0069] "Means of inputting data and sending it to a server" refers to the function of organizing information entered by a user using a terminal and sending it to a server via a network.

[0070] "Means for analyzing the current state of a region" refers to a function where the server uses historical databases to analyze regional population trends and economic indicators, and to identify the current situation and problems.

[0071] "A method for searching for success stories using AI models" refers to a function that uses generative AI models to search for similar success stories from around the world and extract information that matches regional characteristics from among them.

[0072] "Means for generating plans based on regional characteristics and similar cases" refers to the function where the server designs and proposes the optimal redevelopment plan based on identified regional characteristics and successful case studies.

[0073] "A simulation method for predicting the economic effects of a redevelopment plan" refers to a function where the server estimates the economic impact of a proposed redevelopment plan and performs simulations, including risk analysis.

[0074] "Means for evaluating the environmental impact of the plan" refers to the function that allows the server to evaluate the environmental impact of the redevelopment plan and confirm sustainable design elements.

[0075] "Means for evaluating long-term social and economic impacts" refers to the server's ability to analyze and predict the long-term social and economic effects that redevelopment plans will have on the region and its residents.

[0076] This invention is a system for efficiently and sustainably carrying out redevelopment projects in sparsely populated areas and for aging buildings.

[0077] Users input data on the redevelopment area and buildings using a terminal. This data includes the location of the area, population demographics, and the current status of buildings and facilities. Personal computers and tablet devices are used as these terminals, and they are responsible for formatting the data after input and sending it to the server.

[0078] The server interacts with a database to analyze the received data, extracting regional population trends and economic indicators. This process utilizes big data analysis techniques and statistical models. Next, a generative AI model is used to search for similar success stories based on a prompt (e.g., "Please provide examples of successful redevelopment in depopulated areas"). Information on these success stories is retrieved from a data repository in the cloud.

[0079] Subsequently, the server generates multiple redevelopment plans based on regional characteristics and successful case studies. This includes visualizing the designs using specialized CAD software. The generated designs are then subjected to cost-benefit analysis using economic simulations. These simulations include calculations of development costs and expected profits. Furthermore, environmental assessment tools are used to ensure that the redevelopment plans are sustainable for the local community and the environment.

[0080] A concrete example is a redevelopment project for a shopping district in a regional city. When a user inputs location data and current conditions of the shopping district, the server identifies the problem of depopulation and provides similar successful case studies. Furthermore, it generates multiple redevelopment plans tailored to the shopping district, presenting designs that reflect the needs of shop owners and residents. Through simulation and evaluation, it is possible to propose an optimal, environmentally conscious redevelopment plan.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user uses a terminal to input data such as the redevelopment area, building locations, population dynamics, and the current status of facilities. The terminal formats the input data in the appropriate format. It verifies the input data to ensure there are no errors. After the data is formatted, the terminal sends this information to the server via the network.

[0084] Step 2:

[0085] The server stores the received data and analyzes the current situation in the region. The server references the database to extract historical population trends and indicators of economic activity. It also applies statistical models to identify current problems based on the data. The input is regional data received from the user, and the output is a detailed report on the region where problems have been identified.

[0086] Step 3:

[0087] The server runs a generative AI model and searches for similar success stories worldwide using the prompt "Please show me successful examples of redevelopment in sparsely populated areas." The AI ​​model filters the results to select examples that are similar to the characteristics of the region. The input is the result of the regional analysis, and the output is a list of information about the success stories.

[0088] Step 4:

[0089] The server creates a redevelopment plan using a redevelopment proposal generation method based on similar cases. Multiple design options are visualized using CAD software and sent to the user's terminal. The input is data from successful cases, and the output is a visualized redevelopment plan.

[0090] Step 5:

[0091] The server performs simulations to predict the economic impact of a redevelopment plan. It calculates development costs and expected profits, and conducts risk analysis. As a result, it generates a financial indicators report and provides it to the user. The input is the redevelopment plan, and the output is a report predicting the economic impact.

[0092] Step 6:

[0093] The server analyzes the environmental impact of the redevelopment proposal using environmental impact assessment tools. It verifies whether the redevelopment plan includes sustainable design elements and adjusts the design as necessary. The input is the redevelopment plan, and the output is the results of the environmental impact assessment.

[0094] Step 7:

[0095] The server evaluates the long-term effects of a redevelopment plan on the local community and economy. It analyzes the potential for improving residents' quality of life and revitalizing the area, and ultimately provides users with proposals that consider factors contributing to future development. The input is the redevelopment plan, and the output is the result of the long-term impact assessment.

[0096] (Application Example 1)

[0097] 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."

[0098] One challenge is the difficulty in developing concrete plans for the efficient and sustainable redevelopment of areas and buildings facing depopulation and aging infrastructure. Furthermore, there is the difficulty in visually demonstrating the effects and impacts of redevelopment, making it challenging to gain the understanding of stakeholders.

[0099] 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.

[0100] In this invention, the server includes a data receiving means, a regional analysis means, a success case search means, a redevelopment proposal generation means, a financial effect prediction means, an environmental impact assessment means, a long-term impact assessment means, a visual information generation means, and an analysis result display means. This makes it possible to collect and analyze data related to regional redevelopment, present appropriate redevelopment plans, and visually demonstrate their economic effects and environmental impacts.

[0101] A "data receiving means" is a device that has the function of collecting local information provided by the user through their terminal and transferring it to a server.

[0102] A "regional analysis tool" is a tool that has the function of analyzing the current situation and problems of a region based on the received data, and extracting indicators.

[0103] The "success story search method" is a system that uses a generation AI model to search for similar successful redevelopment cases around the world and extracts relevant data.

[0104] A "redevelopment proposal generation tool" is a system that generates redevelopment plans based on regional characteristics and successful case studies, and provides visualized design proposals.

[0105] A "financial effect prediction tool" is a tool that has the function of simulating the economic effects of a proposed redevelopment plan and conducting risk analysis.

[0106] An "environmental impact assessment tool" is a tool that evaluates the environmental impact of a proposed redevelopment plan and has the function of integrating design elements that take sustainability into consideration.

[0107] A "long-term impact assessment tool" is a tool that has the function of evaluating the long-term effects that redevelopment has on local communities and economies.

[0108] A "visual information generation means" is a device that has the function of generating visual data to visually represent redevelopment proposals and their impacts.

[0109] "Analysis result display means" refers to a device that has the function of visually displaying the analyzed results or simulation output to the user.

[0110] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. The system is implemented by users inputting information about the area and buildings from a terminal, which is then processed by a server.

[0111] The server first receives regional information transmitted from terminals using a data receiving device. This information includes location, population dynamics, and the current status of facilities. This data is organized by the server and analyzed by a regional analysis device. The analysis uses historical data to identify indicators of regional population trends and economic activity.

[0112] The success story search mechanism allows the server to utilize a generative AI model to search for similar success stories worldwide and filter them to match the user's needs. The generative AI model uses a database of existing success stories.

[0113] In the redevelopment proposal generation system, the server generates an optimal redevelopment plan based on regional characteristics and successful case studies. This plan is visualized and transmitted to the terminal. Visual information generation is used for visualization, and the plan is proposed as a 3D model.

[0114] Through a financial effect prediction system, the server simulates the economic effects of the redevelopment plan and transmits the results to the terminal via an analysis results display system. At this stage, development costs and expected profits are calculated, and risks are assessed.

[0115] Furthermore, using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Sustainable design elements are considered, and its contribution to long-term regional development is analyzed.

[0116] For example, if a user wants to redevelop a shopping street in a regional city, they can input the location data and current status of the shopping street from their terminal. Based on this information, the server can generate an optimal redevelopment plan and present it as a 3D visual.

[0117] An example of a prompt message is, "Please tell me about appropriate successful case studies and redevelopment plans for local shopping districts."

[0118] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0119] Step 1:

[0120] The user's device inputs information about the region and buildings and sends it to the server via a data receiving device. The input information includes the location of the region, population dynamics, and the current status of the facilities. The server organizes this information and stores it in a database in preparation for the next processing step.

[0121] Step 2:

[0122] The server analyzes the received data using regional analysis tools. The server compares historical data with current information in the database, extracting indicators of population trends and economic activity. The output identifies the current situation in the region and related problems.

[0123] Step 3:

[0124] This system uses a generative AI model to search for successful case studies. The server accesses a database of past successful case studies and searches for similar cases based on the prompt text provided by the user. The prompt text and regional characteristics are used as input, and appropriate successful case studies are selected as output.

[0125] Step 4:

[0126] The redevelopment proposal generation mechanism allows the server to generate redevelopment plans based on regional characteristics and successful case studies. The input consists of regional analysis results and searched successful case studies, and the output is a visualized proposal. Here, a visual information generation mechanism is used to generate a 3D model.

[0127] Step 5:

[0128] This financial impact prediction tool uses a server to simulate the economic effects of a redevelopment plan. Input data includes the redevelopment plan and related financial information. Outputs include development costs, expected benefits, and risk analysis results.

[0129] Step 6:

[0130] Using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Inputs include the redevelopment proposal and related data, and outputs provide environmental impact assessments and long-term socioeconomic effects.

[0131] Step 7:

[0132] The server generates proposals and their evaluation results, which are then transmitted to the user's terminal via an analysis results display device. This allows the user to visually review the details of the redevelopment plan and use this information to help them make a final decision on the redevelopment.

[0133] 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.

[0134] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings, further incorporating an emotion engine that recognizes user emotions. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, long-term impact assessment means, and an emotion engine.

[0135] In the data reception process, the user inputs information about the target area and buildings through a terminal. Data such as location information, resident demographics, and facility status are entered and transmitted to the server by the terminal.

[0136] Regional analysis methods analyze the characteristics and current state of a region based on data received by the server. Population trends and economic conditions are compared with a database to identify current challenges.

[0137] The success story search mechanism uses a generated AI model to search for successful redevelopment cases worldwide. It extracts similar projects and selects the most suitable case for each region.

[0138] In the redevelopment proposal generation system, the server generates redevelopment plans based on regional characteristics and successful case studies. The proposals include design concepts that take into account economic benefits and residents' demands.

[0139] The emotion engine collects user emotion data and incorporates it into redevelopment plans. It adjusts proposals by considering residents' emotional reactions and expectations. This information is extracted from sources such as resident surveys and social media data.

[0140] The financial impact prediction tool uses a server to simulate the economic effects of redevelopment plans. It analyzes the costs, benefits, and risks of each plan and performs an evaluation that incorporates sentiment data.

[0141] Using environmental impact assessment tools, the server evaluates the environmental impact of each redevelopment plan. Sustainable design elements are incorporated, and improvement measures are proposed as needed.

[0142] This long-term impact assessment tool evaluates the long-term impact of the server on local communities and economies. It analyzes the quality of life of residents and the potential for economic development.

[0143] As a concrete example of this system, consider the redevelopment of a shopping street in a regional city. When a user inputs location data and current status of the shopping street, the server identifies the local depopulation challenges and presents similar successful case studies. It generates design proposals and visualizes plans that match the needs of shops and residents. It utilizes an emotion engine to receive feedback from residents and incorporate it into the proposals. As a result, users can select the most suitable redevelopment plan for revitalizing the shopping street and create a plan for its implementation.

[0144] The following describes the processing flow.

[0145] Step 1:

[0146] The user inputs information about the area and buildings targeted for redevelopment into the terminal. Specifically, this includes location information, demographics, and the condition of the buildings. The terminal then organizes this data and prepares it for transmission to the server.

[0147] Step 2:

[0148] The terminal sends the formatted data to the server. The data is structured and sent in a format that is easy for the server to parse.

[0149] Step 3:

[0150] The server receives data and uses regional analysis tools to assess the current state of the region. By referring to historical data, it analyzes demographic trends and changes in economic activity to clarify challenges.

[0151] Step 4:

[0152] The server utilizes a success story search mechanism to search for successful redevelopment cases worldwide using a generating AI model. Similar projects are extracted, and the most suitable case is selected.

[0153] Step 5:

[0154] The server generates redevelopment plans based on regional characteristics and successful case studies using a redevelopment proposal generation system. Multiple design options are proposed, taking into account economic benefits and residents' needs.

[0155] Step 6:

[0156] The server activates the emotion engine and collects user feedback data and public sentiment from relevant information. This information is then used to refine the proposal from an emotional perspective.

[0157] Step 7:

[0158] The server visualizes the redevelopment proposals it generates and sends them to the terminal. The terminal displays the visual design to make it easy for the user to review each proposal.

[0159] Step 8:

[0160] The server uses financial effect prediction tools to simulate the economic impact of each proposal. This includes a cost-benefit analysis for each proposed redevelopment plan.

[0161] Step 9:

[0162] The server will use environmental impact assessment tools to evaluate how the proposed design will affect the environment. Sustainable design elements will be considered, and any areas for improvement will be suggested.

[0163] Step 10:

[0164] The server uses long-term impact assessment tools to evaluate the long-term impact of redevelopment on the region. It analyzes the potential for improving the quality of life for residents and stimulating the economy.

[0165] Step 11:

[0166] Users review analysis results and suggestions sent from the server via their devices and select the optimal redevelopment plan. They then create a plan to implement the redevelopment based on the selected plan.

[0167] (Example 2)

[0168] 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".

[0169] In the redevelopment of sparsely populated areas and aging buildings, there is a need to develop efficient and sustainable plans. Furthermore, it is necessary to create redevelopment projects that appropriately reflect the feelings of residents, thereby improving acceptance and satisfaction within the local community.

[0170] 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.

[0171] In this invention, the server includes means for data input and transmission, means for analyzing regional characteristics and current conditions, means for searching for successful cases using a generative AI model, means for generating redevelopment plans based on regional characteristics and successful cases, means for collecting user sentiment data and reflecting it in the redevelopment plan, means for performing financial simulations of the redevelopment plan, means for evaluating the environmental impact of the redevelopment plan, and means for evaluating the long-term impact on the local community and economy. This makes it possible to formulate efficient, sustainable redevelopment plans that reflect sentiment data.

[0172] "Data input and transmission means" refers to the means by which a user inputs information about a target area or building into a terminal and transmits it to a server.

[0173] "Means for analyzing regional characteristics and current situation" refers to methods for analyzing data in order to understand regional characteristics and recognize current problems.

[0174] "A method for searching for successful cases using a generative AI model" refers to a method of using generative AI to search for successful redevelopment projects from among similar cases.

[0175] "Methods for generating redevelopment plans based on regional characteristics and successful case studies" refers to methods for creating optimal redevelopment plans by combining regional characteristics with past successful case studies.

[0176] "Methods for collecting user emotional data and reflecting it in redevelopment plans" refers to methods for analyzing emotional data obtained from users and utilizing it to improve redevelopment plans.

[0177] "Methods for conducting financial simulations of redevelopment plans" refer to methods for analyzing the economic aspects of redevelopment plans and predicting costs and profits.

[0178] "Means for evaluating the environmental impact of redevelopment plans" refers to means for measuring the environmental impact of each redevelopment plan and ensuring sustainability.

[0179] "Means for assessing the long-term impact on local communities and economies" refers to means of analyzing and providing assessment results for the long-term impact of redevelopment on local communities and economies.

[0180] The following describes embodiments for carrying out this system invention.

[0181] Users input detailed information about the target area and buildings using their devices. This information includes location data, resident demographics, and facility status. The devices transmit this data to a server, which is then used as foundational information for the redevelopment project.

[0182] The server is equipped with hardware for advanced data processing and analyzes regional characteristics and current conditions. This includes identifying challenges in the target region using demographic data and regional economic databases.

[0183] Servers equipped with a generative AI model efficiently search for successful examples of similar redevelopment projects from around the world. The AI ​​model calculates similarity based on the input data and uses prompts to select the most suitable examples.

[0184] Users provide feedback, which is collected on their devices. Emotional data, analyzed through an emotion engine, is reflected in the redevelopment plan. Based on this, the server further refines the redevelopment proposal, creating a plan that meets residents' expectations.

[0185] The server uses financial simulation tools to analyze the costs, benefits, and risks of the redevelopment plan. It also uses environmental impact assessment tools to measure the environmental impact of the redevelopment and construct a sustainable design.

[0186] As a concrete example, when considering the redevelopment of a shopping street in a regional city, the user inputs data on the location and current status of the shopping street. The server analyzes the characteristics of the area, presents successful case studies that can help revitalize the shopping street, and generates design proposals. By utilizing an emotion engine, receiving feedback from residents, and adjusting the proposals, it is possible to create a redevelopment plan that is optimal for revitalizing the shopping street.

[0187] Examples of prompt statements include, "Please provide successful case studies of shopping district redevelopment in regional cities and propose a new plan based on them."

[0188] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0189] Step 1:

[0190] Users input information about the target area and buildings using a terminal. This information includes location data, resident demographics, and facility status. The input data is formatted by the terminal and sent to the server as initial analysis data.

[0191] Step 2:

[0192] The server receives information transmitted from the terminal using a data receiving device. The server then compares the input data with demographic and economic databases to analyze regional characteristics and the current situation. In this process, the server processes the data to identify regional issues and generates analysis results.

[0193] Step 3:

[0194] The server uses a generative AI model to search for similar redevelopment cases. Based on the input data, the AI ​​model performs similarity calculations and extracts appropriate successful cases. A prompt is then used to run the AI ​​model. As a result, a list of the most suitable cases is output.

[0195] Step 4:

[0196] The server generates redevelopment plans based on regional characteristics and successful case studies. The server creates plan prototypes using existing design templates and performs data calculations to reflect economic feasibility and residents' demands. Finally, the proposed plan is generated.

[0197] Step 5:

[0198] Users review initial redevelopment proposals via their devices and provide feedback. This feedback is collected as sentiment data and sent from the device to a server. On the server, a sentiment engine analyzes the data and uses it to refine the proposals.

[0199] Step 6:

[0200] The server performs a financial simulation of the proposed redevelopment plan. It receives details of the proposed plan as input and performs calculations to predict costs, profits, and risks. The resulting financial evaluation is then generated.

[0201] Step 7:

[0202] The server performs environmental impact assessments for each redevelopment plan. It inputs data on environmental burden and sustainability and analyzes it using environmental assessment tools. As output, it provides a report on the degree of environmental impact.

[0203] Step 8:

[0204] The server conducts a long-term impact assessment on the local community and economy. It runs simulations to evaluate the long-term quality of life for residents and the potential for economic growth. The analysis results generate a report on the expected long-term effects.

[0205] (Application Example 2)

[0206] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0207] In the redevelopment of sparsely populated areas and aging buildings, there is a need to quickly generate and propose effective and sustainable redevelopment plans while taking into account the feelings of local residents. In this situation, conventional methods have difficulty adequately incorporating the feelings of local residents, and the lack of sufficient visualization of redevelopment plans makes it difficult to gain the understanding and cooperation of residents.

[0208] 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.

[0209] In this invention, the server includes data receiving means, regional analysis means, success case search means, sentiment data analysis means, virtual reality visualization means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means. This makes it possible to reflect the sentiments of local residents in the redevelopment plan and visualize it using virtual reality technology, thereby achieving effective and sustainable redevelopment while gaining the understanding and cooperation of residents.

[0210] A "data receiving means" is a mechanism for collecting information about regions and buildings provided by users and receiving it in a format that can be processed within the system.

[0211] A "regional analysis tool" is a function that analyzes the characteristics and problems of a region based on the received data and evaluates the current situation.

[0212] The "success story search tool" is a system for searching and referencing past redevelopment projects around the world that have been successful under similar conditions.

[0213] The "redevelopment proposal generation tool" is a component for formulating the most suitable redevelopment plan for a target area, based on analysis results and successful case studies.

[0214] "Emotional data analysis methods" refer to technologies that analyze emotional data collected from local residents and reflect their opinions and feelings in redevelopment plans.

[0215] A "virtual reality visualization device" is a device that uses virtual reality technology to visually represent the generated redevelopment plan in 3D and present it to the user.

[0216] "Financial impact prediction methods" are techniques for predicting the economic impact of a proposed redevelopment plan and for conducting cost-benefit analyses.

[0217] "Environmental impact assessment tools" are a function that evaluates how a redevelopment plan will affect the local natural environment and ecosystem, and takes sustainability into consideration.

[0218] "Long-term impact assessment methods" are evaluation methods that predict the long-term impacts that redevelopment will have on local communities and economies, with the aim of promoting regional development and improving the quality of life for residents.

[0219] To implement this system, users must first input information about the areas and buildings they wish to redevelop using a device such as a smartphone or computer. This input data is received by a data receiving device on the server. The server uses regional analysis tools to analyze the characteristics and current state of the area, and identifies regional issues based on population composition, economic data, etc.

[0220] Next, the server incorporates a success story search mechanism, which uses a generative AI model to search a database of similar redevelopment projects worldwide. This model extracts successful examples from regions with similar conditions, allowing users to select the most effective redevelopment method.

[0221] Furthermore, emotional data acquired from users is analyzed through an emotional data analysis system. This data is collected from resident surveys and social media and is used to measure users' emotional responses to proposals. Based on the results of this analysis, the server uses a redevelopment proposal generation system to create a redevelopment plan that is tailored to the characteristics of the region and the users.

[0222] Furthermore, virtual reality visualization allows the generated plan to be visualized in 3D, enabling users to view the plan in real time within a virtual reality space. This makes it possible for users to visually understand what the specific proposal means to them.

[0223] Financial impact prediction tools predict the economic impact of the generated plans and analyze the balance between costs and benefits. This analysis also takes into account the risks and benefits of the redevelopment proposals. In addition, environmental impact assessment tools evaluate in detail the environmental impact of each plan and take sustainable design into consideration.

[0224] Finally, long-term impact assessment tools are used to evaluate the long-term impacts of the redevelopment on the local community. This allows for a comprehensive determination of whether the redevelopment will improve the quality of life for residents or contribute to economic development.

[0225] As a concrete example of this system, a shopping district in a local city is taken up. When a user inputs data about the shopping district into the system, the server automatically analyzes the local situation and proposes a redevelopment plan based on past successful cases. This plan is visualized using VR technology and optimized based on feedback from residents' sentiment data.

[0226] An example of a prompt statement is as follows:

[0227] "The goal is to redevelop a shopping street in a sparsely populated area. Please generate the optimal redevelopment plan based on emotional feedback received from users. Location information is entered as ___, and residents' emotions are entered as ___."

[0228] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0229] Step 1:

[0230] Users use a terminal to input information about the area and buildings they wish to redevelop. This includes location information, population demographics, and information about surrounding facilities. This data is then transmitted from the terminal to the server.

[0231] Step 2:

[0232] The server receives information sent by users using a data receiving device. The received data is input into a regional analysis device and used as basic data for analyzing regional characteristics and challenges. Here, it is cross-referenced with databases such as demographic data and economic indicators.

[0233] Step 3:

[0234] The server uses a success story search mechanism and leverages a generative AI model to search the database for past successful redevelopment cases similar to the input regional data. During this process, prompts are used to instruct the AI ​​model on specific data search conditions. As a result of the search, a list of relevant case studies is generated.

[0235] Step 4:

[0236] Based on a list of successful cases, the server generates a redevelopment plan using a redevelopment proposal generation method. Here, a plan is created that considers past successes and regional characteristics, while also meeting economic requirements and the needs of local residents. A generating AI model calculates appropriate design and layout.

[0237] Step 5:

[0238] Users input emotional data using their devices. This data, obtained from resident surveys and social media, reflects the expectations and concerns of local residents regarding the redevelopment plan. This data is then transmitted to a server.

[0239] Step 6:

[0240] The server uses emotional data analysis tools to analyze residents' emotional data and feed it back into the redevelopment plan. Based on the analysis results, the plan is adjusted and optimized to be more acceptable to residents.

[0241] Step 7:

[0242] Through virtual reality visualization, the optimized redevelopment plan is visually presented to the user as a 3D model. The user can then use VR technology to view this visualized plan on their device and confirm the details of the specific proposal.

[0243] Step 8:

[0244] The server uses financial impact forecasting tools to simulate the economic impact of the revised plan. It calculates input costs and projected revenues to assess the project's profitability.

[0245] Step 9:

[0246] Using environmental impact assessment tools, the server analyzes the impact of the redevelopment plan on the local environment. From a sustainability perspective, it modifies the plan if necessary.

[0247] Step 10:

[0248] Using long-term impact assessment tools, the server evaluates the long-term effects of the plan on the local community and economy. It makes a comprehensive judgment on whether it will contribute to local development and improvement of residents' lives.

[0249] 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.

[0250] 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.

[0251] 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.

[0252] [Second Embodiment]

[0253] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0254] 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.

[0255] 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).

[0256] 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.

[0257] 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.

[0258] 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).

[0259] 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.

[0260] 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.

[0261] 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.

[0262] 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.

[0263] 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.

[0264] 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".

[0265] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means.

[0266] Regarding the data reception method, users input information about the target area and buildings using a terminal. This information includes, for example, location, population dynamics, and the current status of the facilities. The terminal then compiles this information and sends it to the server.

[0267] In regional analysis, the server uses the received data to analyze the current state of the region. By referring to historical databases, it extracts indicators related to population trends and economic activity, and identifies current problems.

[0268] The success story search mechanism uses a generator AI model to search for successful redevelopment cases around the world. It filters cases similar to regional characteristics and challenges, and provides the relevant data to the user's terminal.

[0269] The redevelopment proposal generation system uses a server to generate an optimal redevelopment plan based on regional characteristics and successful case studies. This proposal includes multiple design options that consider economic effects and residents' needs. The generated design options are visualized and sent to the user's terminal.

[0270] In the financial impact prediction method, the server simulates the economic effects of the proposed redevelopment plan. This includes calculating development costs and expected profits, as well as conducting a risk analysis.

[0271] In environmental impact assessments, the server evaluates the environmental impact of the proposed redevelopment plan. Environmental considerations are taken into account, and sustainable design elements are integrated.

[0272] Long-term impact assessment methods evaluate the long-term effects that servers have on local communities and economies. This involves analyzing the quality of life of residents and the potential for regional revitalization, and considering factors that contribute to future development.

[0273] As an example of this system, consider the process of redeveloping a shopping street in a regional city. When a user inputs location data and current conditions of the shopping street, the server identifies the depopulation problem and provides similar successful case studies. Next, it generates multiple redevelopment plans suitable for the shopping street and visualizes designs tailored to the needs of shops and residents. Furthermore, it simulates the economic effects of each proposal and suggests environmentally conscious designs. Through this process, users can select the appropriate redevelopment plan for revitalizing the shopping street.

[0274] The following describes the process flow.

[0275] Step 1:

[0276] The user inputs information about the target area or building into the terminal. This includes location information, the current facility status, population dynamics, etc.

[0277] Step 2:

[0278] The terminal organizes the input information and transmits it to the server as structured data. Here, data format conversion and transfer according to the necessary protocol are performed.

[0279] Step 3:

[0280] The server analyzes the received data and conducts a current situation assessment using regional analysis means. To identify the economic situation of the region and the issues of residents by comparing with past data, the database is queried.

[0281] Step 4:

[0282] The server uses the successful case search means by leveraging the generated AI model to search for redevelopment cases around the world that match. Similar projects are extracted, and the case most suitable for the regional characteristics is selected.

[0283] Step 5:

[0284] The server uses the redevelopment proposal generation means to generate multiple redevelopment plans from the regional characteristics and successful cases. This includes design plans considering the needs of residents and economic benefits.

[0285] Step 6:

[0286] The server visualizes the generated plans and transmits them to the terminal. The terminal visually presents them so that the user can view and compare each project plan.

[0287] Step 7:

[0288] The server uses financial effect prediction tools to simulate the economic impact of the redevelopment plan. For each proposed plan, it performs a cost analysis and calculates the expected profits.

[0289] Step 8:

[0290] The server uses environmental impact assessment tools to evaluate the environmental impact of each redevelopment plan. It verifies whether sustainable design elements are incorporated into the proposal and suggests improvements as needed.

[0291] Step 9:

[0292] The long-term impact of the server on local communities and economies will be evaluated using long-term impact assessment methods. The potential for improving the quality of life for local residents and stimulating the economy will be analyzed.

[0293] Step 10:

[0294] Users receive various reports via their devices and select the most suitable option from several proposed redevelopment plans. Through this process, effective redevelopment aimed at sustainable regional development is carried out.

[0295] (Example 1)

[0296] 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."

[0297] Redeveloping sparsely populated areas and dilapidated buildings presents challenges in formulating appropriate plans tailored to local characteristics. It requires ensuring economic and environmental sustainability while delivering long-term benefits to the local community. However, previous redevelopment projects have struggled to quickly process extensive data and conduct accurate analysis and evaluation, thus failing to derive optimal redevelopment strategies.

[0298] 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.

[0299] In this invention, the server includes means for inputting and transmitting data to the server, means for analyzing the current situation in the region, and means for searching for successful cases using an AI model. This makes it possible to quickly generate optimal redevelopment plans tailored to regional characteristics and provide sustainable redevelopment measures by conducting economic and environmental evaluations.

[0300] "Means of inputting data and sending it to a server" refers to the function of organizing information entered by a user using a terminal and sending it to a server via a network.

[0301] "Means for analyzing the current state of a region" refers to a function where the server uses historical databases to analyze regional population trends and economic indicators, and to identify the current situation and problems.

[0302] "A method for searching for success stories using AI models" refers to a function that uses generative AI models to search for similar success stories from around the world and extract information that matches regional characteristics from among them.

[0303] "Means for generating plans based on regional characteristics and similar cases" refers to the function where the server designs and proposes the optimal redevelopment plan based on identified regional characteristics and successful case studies.

[0304] "A simulation method for predicting the economic effects of a redevelopment plan" refers to a function where the server estimates the economic impact of a proposed redevelopment plan and performs simulations, including risk analysis.

[0305] "Means for evaluating the environmental impact of the plan" refers to the function that allows the server to evaluate the environmental impact of the redevelopment plan and confirm sustainable design elements.

[0306] The term "means for evaluating long-term social and economic impacts" refers to the function of the server to analyze and predict the long-term social and economic effects that the redevelopment plan has on the region and its residents.

[0307] This invention is a system for efficiently and sustainably promoting redevelopment projects in depopulated areas and aging buildings.

[0308] The user uses a terminal to input data on the region or building targeted for redevelopment. The data to be input includes the location of the region, population dynamics, and the current situation of buildings and facilities. As this terminal, a personal computer or a tablet terminal is used, and after inputting the data, it plays the role of formatting and transmitting it to the server.

[0309] The server cooperates with a database to extract the population trends and economic indicators of the region in order to analyze the received data. Big data analysis techniques and statistical models are used in this process. Next, using the generated AI model, similar successful cases are searched based on a prompt sentence (e.g., "Please show successful cases of depopulated area redevelopment"). Information on successful cases refers to a data repository on the cloud.

[0310] After that, the server generates multiple redevelopment plans based on the regional characteristics and successful cases. This includes visualizing the design using dedicated CAD software. The generated design plan is predicted for cost-effectiveness through economic simulation. This simulation includes calculating the development cost and expected benefits. Furthermore, an environmental assessment tool is used to confirm that the redevelopment plan is sustainable for the local community and environment.

[0311] A concrete example is a redevelopment project for a shopping district in a regional city. When a user inputs location data and current conditions of the shopping district, the server identifies the problem of depopulation and provides similar successful case studies. Furthermore, it generates multiple redevelopment plans tailored to the shopping district, presenting designs that reflect the needs of shop owners and residents. Through simulation and evaluation, it is possible to propose an optimal, environmentally conscious redevelopment plan.

[0312] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0313] Step 1:

[0314] The user uses a terminal to input data such as the redevelopment area, building locations, population dynamics, and the current status of facilities. The terminal formats the input data in the appropriate format. It verifies the input data to ensure there are no errors. After the data is formatted, the terminal sends this information to the server via the network.

[0315] Step 2:

[0316] The server stores the received data and analyzes the current situation in the region. The server references the database to extract historical population trends and indicators of economic activity. It also applies statistical models to identify current problems based on the data. The input is regional data received from the user, and the output is a detailed report on the region where problems have been identified.

[0317] Step 3:

[0318] The server runs a generative AI model and searches for similar success stories worldwide using the prompt "Please show me successful examples of redevelopment in sparsely populated areas." The AI ​​model filters the results to select examples that are similar to the characteristics of the region. The input is the result of the regional analysis, and the output is a list of information about the success stories.

[0319] Step 4:

[0320] The server creates a redevelopment plan using a redevelopment proposal generation method based on similar cases. Multiple design options are visualized using CAD software and sent to the user's terminal. The input is data from successful cases, and the output is a visualized redevelopment plan.

[0321] Step 5:

[0322] The server performs simulations to predict the economic impact of a redevelopment plan. It calculates development costs and expected profits, and conducts risk analysis. As a result, it generates a financial indicators report and provides it to the user. The input is the redevelopment plan, and the output is a report predicting the economic impact.

[0323] Step 6:

[0324] The server analyzes the environmental impact of the redevelopment proposal using environmental impact assessment tools. It verifies whether the redevelopment plan includes sustainable design elements and adjusts the design as necessary. The input is the redevelopment plan, and the output is the results of the environmental impact assessment.

[0325] Step 7:

[0326] The server evaluates the long-term effects of a redevelopment plan on the local community and economy. It analyzes the potential for improving residents' quality of life and revitalizing the area, and ultimately provides users with proposals that consider factors contributing to future development. The input is the redevelopment plan, and the output is the result of the long-term impact assessment.

[0327] (Application Example 1)

[0328] 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."

[0329] One challenge is the difficulty in developing concrete plans for the efficient and sustainable redevelopment of areas and buildings facing depopulation and aging infrastructure. Furthermore, there is the difficulty in visually demonstrating the effects and impacts of redevelopment, making it challenging to gain the understanding of stakeholders.

[0330] 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.

[0331] In this invention, the server includes a data receiving means, a regional analysis means, a success case search means, a redevelopment proposal generation means, a financial effect prediction means, an environmental impact assessment means, a long-term impact assessment means, a visual information generation means, and an analysis result display means. This makes it possible to collect and analyze data related to regional redevelopment, present appropriate redevelopment plans, and visually demonstrate their economic effects and environmental impacts.

[0332] A "data receiving means" is a device that has the function of collecting local information provided by the user through their terminal and transferring it to a server.

[0333] A "regional analysis tool" is a tool that has the function of analyzing the current situation and problems of a region based on the received data, and extracting indicators.

[0334] The "success story search method" is a system that uses a generation AI model to search for similar successful redevelopment cases around the world and extracts relevant data.

[0335] A "redevelopment proposal generation tool" is a system that generates redevelopment plans based on regional characteristics and successful case studies, and provides visualized design proposals.

[0336] A "financial effect prediction tool" is a tool that has the function of simulating the economic effects of a proposed redevelopment plan and conducting risk analysis.

[0337] An "environmental impact assessment tool" is a tool that evaluates the environmental impact of a proposed redevelopment plan and has the function of integrating design elements that take sustainability into consideration.

[0338] A "long-term impact assessment tool" is a tool that has the function of evaluating the long-term effects that redevelopment has on local communities and economies.

[0339] A "visual information generation means" is a device that has the function of generating visual data to visually represent redevelopment proposals and their impacts.

[0340] "Analysis result display means" refers to a device that has the function of visually displaying the analyzed results or simulation output to the user.

[0341] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. The system is implemented by users inputting information about the area and buildings from a terminal, which is then processed by a server.

[0342] The server first receives regional information transmitted from terminals using a data receiving device. This information includes location, population dynamics, and the current status of facilities. This data is organized by the server and analyzed by a regional analysis device. The analysis uses historical data to identify indicators of regional population trends and economic activity.

[0343] The success story search mechanism allows the server to utilize a generative AI model to search for similar success stories worldwide and filter them to match the user's needs. The generative AI model uses a database of existing success stories.

[0344] In the redevelopment proposal generation system, the server generates an optimal redevelopment plan based on regional characteristics and successful case studies. This plan is visualized and transmitted to the terminal. Visual information generation is used for visualization, and the plan is proposed as a 3D model.

[0345] Through a financial effect prediction system, the server simulates the economic effects of the redevelopment plan and transmits the results to the terminal via an analysis results display system. At this stage, development costs and expected profits are calculated, and risks are assessed.

[0346] Furthermore, using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Sustainable design elements are considered, and its contribution to long-term regional development is analyzed.

[0347] For example, if a user wants to redevelop a shopping street in a regional city, they can input the location data and current status of the shopping street from their terminal. Based on this information, the server can generate an optimal redevelopment plan and present it as a 3D visual.

[0348] An example of a prompt message is, "Please tell me about appropriate successful case studies and redevelopment plans for local shopping districts."

[0349] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0350] Step 1:

[0351] The user's device inputs information about the region and buildings and sends it to the server via a data receiving device. The input information includes the location of the region, population dynamics, and the current status of the facilities. The server organizes this information and stores it in a database in preparation for the next processing step.

[0352] Step 2:

[0353] The server analyzes the received data using regional analysis tools. The server compares historical data with current information in the database, extracting indicators of population trends and economic activity. The output identifies the current situation in the region and related problems.

[0354] Step 3:

[0355] This system uses a generative AI model to search for successful case studies. The server accesses a database of past successful case studies and searches for similar cases based on the prompt text provided by the user. The prompt text and regional characteristics are used as input, and appropriate successful case studies are selected as output.

[0356] Step 4:

[0357] The redevelopment proposal generation mechanism allows the server to generate redevelopment plans based on regional characteristics and successful case studies. The input consists of regional analysis results and searched successful case studies, and the output is a visualized proposal. Here, a visual information generation mechanism is used to generate a 3D model.

[0358] Step 5:

[0359] This financial impact prediction tool uses a server to simulate the economic effects of a redevelopment plan. Input data includes the redevelopment plan and related financial information. Outputs include development costs, expected benefits, and risk analysis results.

[0360] Step 6:

[0361] Using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Inputs include the redevelopment proposal and related data, and outputs provide environmental impact assessments and long-term socioeconomic effects.

[0362] Step 7:

[0363] The server generates proposals and their evaluation results, which are then transmitted to the user's terminal via an analysis results display device. This allows the user to visually review the details of the redevelopment plan and use this information to help them make a final decision on the redevelopment.

[0364] 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.

[0365] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings, further incorporating an emotion engine that recognizes user emotions. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, long-term impact assessment means, and an emotion engine.

[0366] In the data reception process, the user inputs information about the target area and buildings through a terminal. Data such as location information, resident demographics, and facility status are entered and transmitted to the server by the terminal.

[0367] Regional analysis methods analyze the characteristics and current state of a region based on data received by the server. Population trends and economic conditions are compared with a database to identify current challenges.

[0368] The success story search mechanism uses a generated AI model to search for successful redevelopment cases worldwide. It extracts similar projects and selects the most suitable case for each region.

[0369] In the redevelopment proposal generation system, the server generates redevelopment plans based on regional characteristics and successful case studies. The proposals include design concepts that take into account economic benefits and residents' demands.

[0370] The emotion engine collects user emotion data and incorporates it into redevelopment plans. It adjusts proposals by considering residents' emotional reactions and expectations. This information is extracted from sources such as resident surveys and social media data.

[0371] The financial impact prediction tool uses a server to simulate the economic effects of redevelopment plans. It analyzes the costs, benefits, and risks of each plan and performs an evaluation that incorporates sentiment data.

[0372] Using environmental impact assessment tools, the server evaluates the environmental impact of each redevelopment plan. Sustainable design elements are incorporated, and improvement measures are proposed as needed.

[0373] This long-term impact assessment tool evaluates the long-term impact of the server on local communities and economies. It analyzes the quality of life of residents and the potential for economic development.

[0374] As a concrete example of this system, consider the redevelopment of a shopping street in a regional city. When a user inputs location data and current status of the shopping street, the server identifies the local depopulation challenges and presents similar successful case studies. It generates design proposals and visualizes plans that match the needs of shops and residents. It utilizes an emotion engine to receive feedback from residents and incorporate it into the proposals. As a result, users can select the most suitable redevelopment plan for revitalizing the shopping street and create a plan for its implementation.

[0375] The following describes the processing flow.

[0376] Step 1:

[0377] The user inputs information about the area and buildings targeted for redevelopment into the terminal. Specifically, this includes location information, demographics, and the condition of the buildings. The terminal then organizes this data and prepares it for transmission to the server.

[0378] Step 2:

[0379] The terminal sends the formatted data to the server. The data is structured and sent in a format that is easy for the server to parse.

[0380] Step 3:

[0381] The server receives data and uses regional analysis tools to assess the current state of the region. By referring to historical data, it analyzes demographic trends and changes in economic activity to clarify challenges.

[0382] Step 4:

[0383] The server utilizes a success story search mechanism to search for successful redevelopment cases worldwide using a generating AI model. Similar projects are extracted, and the most suitable case is selected.

[0384] Step 5:

[0385] The server generates redevelopment plans based on regional characteristics and successful case studies using a redevelopment proposal generation system. Multiple design options are proposed, taking into account economic benefits and residents' needs.

[0386] Step 6:

[0387] The server activates the emotion engine and collects user feedback data and public sentiment from relevant information. This information is then used to refine the proposal from an emotional perspective.

[0388] Step 7:

[0389] The server visualizes the redevelopment proposals it generates and sends them to the terminal. The terminal displays the visual design to make it easy for the user to review each proposal.

[0390] Step 8:

[0391] The server uses financial effect prediction tools to simulate the economic impact of each proposal. This includes a cost-benefit analysis for each proposed redevelopment plan.

[0392] Step 9:

[0393] The server will use environmental impact assessment tools to evaluate how the proposed design will affect the environment. Sustainable design elements will be considered, and any areas for improvement will be suggested.

[0394] Step 10:

[0395] The server uses long-term impact assessment tools to evaluate the long-term impact of redevelopment on the region. It analyzes the potential for improving the quality of life for residents and stimulating the economy.

[0396] Step 11:

[0397] Users review analysis results and suggestions sent from the server via their devices and select the optimal redevelopment plan. They then create a plan to implement the redevelopment based on the selected plan.

[0398] (Example 2)

[0399] 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".

[0400] In the redevelopment of sparsely populated areas and aging buildings, there is a need to develop efficient and sustainable plans. Furthermore, it is necessary to create redevelopment projects that appropriately reflect the feelings of residents, thereby improving acceptance and satisfaction within the local community.

[0401] 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.

[0402] In this invention, the server includes means for data input and transmission, means for analyzing regional characteristics and current conditions, means for searching for successful cases using a generative AI model, means for generating redevelopment plans based on regional characteristics and successful cases, means for collecting user sentiment data and reflecting it in the redevelopment plan, means for performing financial simulations of the redevelopment plan, means for evaluating the environmental impact of the redevelopment plan, and means for evaluating the long-term impact on the local community and economy. This makes it possible to formulate efficient, sustainable redevelopment plans that reflect sentiment data.

[0403] "Data input and transmission means" refers to the means by which a user inputs information about a target area or building into a terminal and transmits it to a server.

[0404] "Means for analyzing regional characteristics and current situation" refers to methods for analyzing data in order to understand regional characteristics and recognize current problems.

[0405] "A method for searching for successful cases using a generative AI model" refers to a method of using generative AI to search for successful redevelopment projects from among similar cases.

[0406] "Methods for generating redevelopment plans based on regional characteristics and successful case studies" refers to methods for creating optimal redevelopment plans by combining regional characteristics with past successful case studies.

[0407] "Methods for collecting user emotional data and reflecting it in redevelopment plans" refers to methods for analyzing emotional data obtained from users and utilizing it to improve redevelopment plans.

[0408] "Methods for conducting financial simulations of redevelopment plans" refer to methods for analyzing the economic aspects of redevelopment plans and predicting costs and profits.

[0409] "Means for evaluating the environmental impact of redevelopment plans" refers to means for measuring the environmental impact of each redevelopment plan and ensuring sustainability.

[0410] "Means for assessing the long-term impact on local communities and economies" refers to means of analyzing and providing assessment results for the long-term impact of redevelopment on local communities and economies.

[0411] The following describes embodiments for carrying out this system invention.

[0412] Users input detailed information about the target area and buildings using their devices. This information includes location data, resident demographics, and facility status. The devices transmit this data to a server, which is then used as foundational information for the redevelopment project.

[0413] The server is equipped with hardware for advanced data processing and analyzes regional characteristics and current conditions. This includes identifying challenges in the target region using demographic data and regional economic databases.

[0414] Servers equipped with a generative AI model efficiently search for successful examples of similar redevelopment projects from around the world. The AI ​​model calculates similarity based on the input data and uses prompts to select the most suitable examples.

[0415] Users provide feedback, which is collected on their devices. Emotional data, analyzed through an emotion engine, is reflected in the redevelopment plan. Based on this, the server further refines the redevelopment proposal, creating a plan that meets residents' expectations.

[0416] The server uses financial simulation tools to analyze the costs, benefits, and risks of the redevelopment plan. It also uses environmental impact assessment tools to measure the environmental impact of the redevelopment and construct a sustainable design.

[0417] As a concrete example, when considering the redevelopment of a shopping street in a regional city, the user inputs data on the location and current status of the shopping street. The server analyzes the characteristics of the area, presents successful case studies that can help revitalize the shopping street, and generates design proposals. By utilizing an emotion engine, receiving feedback from residents, and adjusting the proposals, it is possible to create a redevelopment plan that is optimal for revitalizing the shopping street.

[0418] Examples of prompt statements include, "Please provide successful case studies of shopping district redevelopment in regional cities and propose a new plan based on them."

[0419] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0420] Step 1:

[0421] Users input information about the target area and buildings using a terminal. This information includes location data, resident demographics, and facility status. The input data is formatted by the terminal and sent to the server as initial analysis data.

[0422] Step 2:

[0423] The server receives information transmitted from the terminal using a data receiving device. The server then compares the input data with demographic and economic databases to analyze regional characteristics and the current situation. In this process, the server processes the data to identify regional issues and generates analysis results.

[0424] Step 3:

[0425] The server uses a generative AI model to search for similar redevelopment cases. Based on the input data, the AI ​​model performs similarity calculations and extracts appropriate successful cases. A prompt is then used to run the AI ​​model. As a result, a list of the most suitable cases is output.

[0426] Step 4:

[0427] The server generates redevelopment plans based on regional characteristics and successful case studies. The server creates plan prototypes using existing design templates and performs data calculations to reflect economic feasibility and residents' demands. Finally, the proposed plan is generated.

[0428] Step 5:

[0429] Users review initial redevelopment proposals via their devices and provide feedback. This feedback is collected as sentiment data and sent from the device to a server. On the server, a sentiment engine analyzes the data and uses it to refine the proposals.

[0430] Step 6:

[0431] The server performs a financial simulation of the proposed redevelopment plan. It receives details of the proposed plan as input and performs calculations to predict costs, profits, and risks. The resulting financial evaluation is then generated.

[0432] Step 7:

[0433] The server performs environmental impact assessments for each redevelopment plan. It inputs data on environmental burden and sustainability and analyzes it using environmental assessment tools. As output, it provides a report on the degree of environmental impact.

[0434] Step 8:

[0435] The server conducts a long-term impact assessment on the local community and economy. It runs simulations to evaluate the long-term quality of life for residents and the potential for economic growth. The analysis results generate a report on the expected long-term effects.

[0436] (Application Example 2)

[0437] 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."

[0438] In the redevelopment of sparsely populated areas and aging buildings, there is a need to quickly generate and propose effective and sustainable redevelopment plans while taking into account the feelings of local residents. In this situation, conventional methods have difficulty adequately incorporating the feelings of local residents, and the lack of sufficient visualization of redevelopment plans makes it difficult to gain the understanding and cooperation of residents.

[0439] 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.

[0440] In this invention, the server includes data receiving means, regional analysis means, success case search means, sentiment data analysis means, virtual reality visualization means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means. This makes it possible to reflect the sentiments of local residents in the redevelopment plan and visualize it using virtual reality technology, thereby achieving effective and sustainable redevelopment while gaining the understanding and cooperation of residents.

[0441] A "data receiving means" is a mechanism for collecting information about regions and buildings provided by users and receiving it in a format that can be processed within the system.

[0442] A "regional analysis tool" is a function that analyzes the characteristics and problems of a region based on the received data and evaluates the current situation.

[0443] The "success story search tool" is a system for searching and referencing past redevelopment projects around the world that have been successful under similar conditions.

[0444] The "redevelopment proposal generation tool" is a component for formulating the most suitable redevelopment plan for a target area, based on analysis results and successful case studies.

[0445] "Emotional data analysis methods" refer to technologies that analyze emotional data collected from local residents and reflect their opinions and feelings in redevelopment plans.

[0446] A "virtual reality visualization device" is a device that uses virtual reality technology to visually represent the generated redevelopment plan in 3D and present it to the user.

[0447] "Financial impact prediction methods" are techniques for predicting the economic impact of a proposed redevelopment plan and for conducting cost-benefit analyses.

[0448] "Environmental impact assessment tools" are a function that evaluates how a redevelopment plan will affect the local natural environment and ecosystem, and takes sustainability into consideration.

[0449] "Long-term impact assessment methods" are evaluation methods that predict the long-term impacts that redevelopment will have on local communities and economies, with the aim of promoting regional development and improving the quality of life for residents.

[0450] To implement this system, users must first input information about the areas and buildings they wish to redevelop using a device such as a smartphone or computer. This input data is received by a data receiving device on the server. The server uses regional analysis tools to analyze the characteristics and current state of the area, and identifies regional issues based on population composition, economic data, etc.

[0451] Next, the server incorporates a success story search mechanism, which uses a generative AI model to search a database of similar redevelopment projects worldwide. This model extracts successful examples from regions with similar conditions, allowing users to select the most effective redevelopment method.

[0452] Furthermore, emotional data acquired from users is analyzed through an emotional data analysis system. This data is collected from resident surveys and social media and is used to measure users' emotional responses to proposals. Based on the results of this analysis, the server uses a redevelopment proposal generation system to create a redevelopment plan that is tailored to the characteristics of the region and the users.

[0453] Furthermore, virtual reality visualization allows the generated plan to be visualized in 3D, enabling users to view the plan in real time within a virtual reality space. This makes it possible for users to visually understand what the specific proposal means to them.

[0454] Financial impact prediction tools predict the economic impact of the generated plans and analyze the balance between costs and benefits. This analysis also takes into account the risks and benefits of the redevelopment proposals. In addition, environmental impact assessment tools evaluate in detail the environmental impact of each plan and take sustainable design into consideration.

[0455] Finally, long-term impact assessment tools are used to evaluate the long-term impacts of the redevelopment on the local community. This allows for a comprehensive determination of whether the redevelopment will improve the quality of life for residents or contribute to economic development.

[0456] As a concrete example of this system, a shopping district in a local city is taken up. When a user inputs data about the shopping district into the system, the server automatically analyzes the local situation and proposes a redevelopment plan based on past successful cases. This plan is visualized using VR technology and optimized based on feedback from residents' sentiment data.

[0457] An example of a prompt statement is as follows:

[0458] "The goal is to redevelop a shopping street in a sparsely populated area. Please generate the optimal redevelopment plan based on emotional feedback received from users. Location information is entered as ___, and residents' emotions are entered as ___."

[0459] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0460] Step 1:

[0461] Users use a terminal to input information about the area and buildings they wish to redevelop. This includes location information, population demographics, and information about surrounding facilities. This data is then transmitted from the terminal to the server.

[0462] Step 2:

[0463] The server receives information sent by users using a data receiving device. The received data is input into a regional analysis device and used as basic data for analyzing regional characteristics and challenges. Here, it is cross-referenced with databases such as demographic data and economic indicators.

[0464] Step 3:

[0465] The server uses a success story search mechanism and leverages a generative AI model to search the database for past successful redevelopment cases similar to the input regional data. During this process, prompts are used to instruct the AI ​​model on specific data search conditions. As a result of the search, a list of relevant case studies is generated.

[0466] Step 4:

[0467] Based on a list of successful cases, the server generates a redevelopment plan using a redevelopment proposal generation method. Here, a plan is created that considers past successes and regional characteristics, while also meeting economic requirements and the needs of local residents. A generating AI model calculates appropriate design and layout.

[0468] Step 5:

[0469] Users input emotional data using their devices. This data, obtained from resident surveys and social media, reflects the expectations and concerns of local residents regarding the redevelopment plan. This data is then transmitted to a server.

[0470] Step 6:

[0471] The server uses emotional data analysis tools to analyze residents' emotional data and feed it back into the redevelopment plan. Based on the analysis results, the plan is adjusted and optimized to be more acceptable to residents.

[0472] Step 7:

[0473] Through virtual reality visualization, the optimized redevelopment plan is visually presented to the user as a 3D model. The user can then use VR technology to view this visualized plan on their device and confirm the details of the specific proposal.

[0474] Step 8:

[0475] The server uses financial impact forecasting tools to simulate the economic impact of the revised plan. It calculates input costs and projected revenues to assess the project's profitability.

[0476] Step 9:

[0477] Using environmental impact assessment tools, the server analyzes the impact of the redevelopment plan on the local environment. From a sustainability perspective, it modifies the plan if necessary.

[0478] Step 10:

[0479] Using long-term impact assessment tools, the server evaluates the long-term effects of the plan on the local community and economy. It makes a comprehensive judgment on whether it will contribute to local development and improvement of residents' lives.

[0480] 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.

[0481] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0482] 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.

[0483] [Third Embodiment]

[0484] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0485] 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.

[0486] 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).

[0487] 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.

[0488] 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.

[0489] 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).

[0490] 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.

[0491] 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.

[0492] 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.

[0493] 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.

[0494] 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.

[0495] 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".

[0496] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means.

[0497] Regarding the data reception method, users input information about the target area and buildings using a terminal. This information includes, for example, location, population dynamics, and the current status of the facilities. The terminal then compiles this information and sends it to the server.

[0498] In regional analysis, the server uses the received data to analyze the current state of the region. By referring to historical databases, it extracts indicators related to population trends and economic activity, and identifies current problems.

[0499] The success story search mechanism uses a generator AI model to search for successful redevelopment cases around the world. It filters cases similar to regional characteristics and challenges, and provides the relevant data to the user's terminal.

[0500] The redevelopment proposal generation system uses a server to generate an optimal redevelopment plan based on regional characteristics and successful case studies. This proposal includes multiple design options that consider economic effects and residents' needs. The generated design options are visualized and sent to the user's terminal.

[0501] In the financial impact prediction method, the server simulates the economic effects of the proposed redevelopment plan. This includes calculating development costs and expected profits, as well as conducting a risk analysis.

[0502] In environmental impact assessments, the server evaluates the environmental impact of the proposed redevelopment plan. Environmental considerations are taken into account, and sustainable design elements are integrated.

[0503] Long-term impact assessment methods evaluate the long-term effects that servers have on local communities and economies. This involves analyzing the quality of life of residents and the potential for regional revitalization, and considering factors that contribute to future development.

[0504] As an example of this system, consider the process of redeveloping a shopping street in a regional city. When a user inputs location data and current conditions of the shopping street, the server identifies the depopulation problem and provides similar successful case studies. Next, it generates multiple redevelopment plans suitable for the shopping street and visualizes designs tailored to the needs of shops and residents. Furthermore, it simulates the economic effects of each proposal and suggests environmentally conscious designs. Through this process, users can select the appropriate redevelopment plan for revitalizing the shopping street.

[0505] The following describes the processing flow.

[0506] Step 1:

[0507] The user inputs information about the target area or building into the device. This includes location information, current facility status, and demographic data.

[0508] Step 2:

[0509] The terminal processes the input information and sends it to the server as structured data. This involves data format conversion and transfer according to the necessary protocols.

[0510] Step 3:

[0511] The server analyzes the received data and uses regional analysis tools to assess the current situation. It compares this data with past data and cross-references it with databases to identify regional economic conditions and challenges faced by residents.

[0512] Step 4:

[0513] The server uses a generation AI model and a success story search method to find matching redevelopment cases around the world. It extracts similar projects and selects the case that is best suited to the regional characteristics.

[0514] Step 5:

[0515] The server uses a redevelopment proposal generation system to generate multiple redevelopment plans based on regional characteristics and successful case studies. These plans include design proposals that take into account the needs and economic benefits of the residents.

[0516] Step 6:

[0517] The server visualizes the generated proposals and sends them to the terminal. The terminal visually presents each project proposal so that the user can view and compare them.

[0518] Step 7:

[0519] The server uses financial effect prediction tools to simulate the economic impact of the redevelopment plan. For each proposed plan, it performs a cost analysis and calculates the expected profits.

[0520] Step 8:

[0521] The server uses environmental impact assessment tools to evaluate the environmental impact of each redevelopment plan. It verifies whether sustainable design elements are incorporated into the proposal and suggests improvements as needed.

[0522] Step 9:

[0523] The long-term impact of the server on local communities and economies will be evaluated using long-term impact assessment methods. The potential for improving the quality of life for local residents and stimulating the economy will be analyzed.

[0524] Step 10:

[0525] Users receive various reports via their devices and select the most suitable option from several proposed redevelopment plans. Through this process, effective redevelopment aimed at sustainable regional development is carried out.

[0526] (Example 1)

[0527] 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."

[0528] Redeveloping sparsely populated areas and dilapidated buildings presents challenges in formulating appropriate plans tailored to local characteristics. It requires ensuring economic and environmental sustainability while delivering long-term benefits to the local community. However, previous redevelopment projects have struggled to quickly process extensive data and conduct accurate analysis and evaluation, thus failing to derive optimal redevelopment strategies.

[0529] 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.

[0530] In this invention, the server includes means for inputting and transmitting data to the server, means for analyzing the current situation in the region, and means for searching for successful cases using an AI model. This makes it possible to quickly generate optimal redevelopment plans tailored to regional characteristics and provide sustainable redevelopment measures by conducting economic and environmental evaluations.

[0531] "Means of inputting data and sending it to a server" refers to the function of organizing information entered by a user using a terminal and sending it to a server via a network.

[0532] "Means for analyzing the current state of a region" refers to a function where the server uses historical databases to analyze regional population trends and economic indicators, and to identify the current situation and problems.

[0533] "A method for searching for success stories using AI models" refers to a function that uses generative AI models to search for similar success stories from around the world and extract information that matches regional characteristics from among them.

[0534] "Means for generating plans based on regional characteristics and similar cases" refers to the function where the server designs and proposes the optimal redevelopment plan based on identified regional characteristics and successful case studies.

[0535] "A simulation method for predicting the economic effects of a redevelopment plan" refers to a function where the server estimates the economic impact of a proposed redevelopment plan and performs simulations, including risk analysis.

[0536] "Means for evaluating the environmental impact of the plan" refers to the function that allows the server to evaluate the environmental impact of the redevelopment plan and confirm sustainable design elements.

[0537] "Means for evaluating long-term social and economic impacts" refers to the server's ability to analyze and predict the long-term social and economic effects that redevelopment plans will have on the region and its residents.

[0538] This invention is a system for efficiently and sustainably carrying out redevelopment projects in sparsely populated areas and for aging buildings.

[0539] Users input data on the redevelopment area and buildings using a terminal. This data includes the location of the area, population demographics, and the current status of buildings and facilities. Personal computers and tablet devices are used as these terminals, and they are responsible for formatting the data after input and sending it to the server.

[0540] The server interacts with a database to analyze the received data, extracting regional population trends and economic indicators. This process utilizes big data analysis techniques and statistical models. Next, a generative AI model is used to search for similar success stories based on a prompt (e.g., "Please provide examples of successful redevelopment in depopulated areas"). Information on these success stories is retrieved from a data repository in the cloud.

[0541] Subsequently, the server generates multiple redevelopment plans based on regional characteristics and successful case studies. This includes visualizing the designs using specialized CAD software. The generated designs are then subjected to cost-benefit analysis using economic simulations. These simulations include calculations of development costs and expected profits. Furthermore, environmental assessment tools are used to ensure that the redevelopment plans are sustainable for the local community and the environment.

[0542] A concrete example is a redevelopment project for a shopping district in a regional city. When a user inputs location data and current conditions of the shopping district, the server identifies the problem of depopulation and provides similar successful case studies. Furthermore, it generates multiple redevelopment plans tailored to the shopping district, presenting designs that reflect the needs of shop owners and residents. Through simulation and evaluation, it is possible to propose an optimal, environmentally conscious redevelopment plan.

[0543] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0544] Step 1:

[0545] The user uses a terminal to input data such as the redevelopment area, building locations, population dynamics, and the current status of facilities. The terminal formats the input data in the appropriate format. It verifies the input data to ensure there are no errors. After the data is formatted, the terminal sends this information to the server via the network.

[0546] Step 2:

[0547] The server stores the received data and analyzes the current situation in the region. The server references the database to extract historical population trends and indicators of economic activity. It also applies statistical models to identify current problems based on the data. The input is regional data received from the user, and the output is a detailed report on the region where problems have been identified.

[0548] Step 3:

[0549] The server runs a generative AI model and searches for similar success stories worldwide using the prompt "Please show me successful examples of redevelopment in sparsely populated areas." The AI ​​model filters the results to select examples that are similar to the characteristics of the region. The input is the result of the regional analysis, and the output is a list of information about the success stories.

[0550] Step 4:

[0551] The server creates a redevelopment plan using a redevelopment proposal generation method based on similar cases. Multiple design options are visualized using CAD software and sent to the user's terminal. The input is data from successful cases, and the output is a visualized redevelopment plan.

[0552] Step 5:

[0553] The server performs simulations to predict the economic impact of a redevelopment plan. It calculates development costs and expected profits, and conducts risk analysis. As a result, it generates a financial indicators report and provides it to the user. The input is the redevelopment plan, and the output is a report predicting the economic impact.

[0554] Step 6:

[0555] The server analyzes the environmental impact of the redevelopment proposal using environmental impact assessment tools. It verifies whether the redevelopment plan includes sustainable design elements and adjusts the design as necessary. The input is the redevelopment plan, and the output is the results of the environmental impact assessment.

[0556] Step 7:

[0557] The server evaluates the long-term effects of a redevelopment plan on the local community and economy. It analyzes the potential for improving residents' quality of life and revitalizing the area, and ultimately provides users with proposals that consider factors contributing to future development. The input is the redevelopment plan, and the output is the result of the long-term impact assessment.

[0558] (Application Example 1)

[0559] 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."

[0560] One challenge is the difficulty in developing concrete plans for the efficient and sustainable redevelopment of areas and buildings facing depopulation and aging infrastructure. Furthermore, there is the difficulty in visually demonstrating the effects and impacts of redevelopment, making it challenging to gain the understanding of stakeholders.

[0561] 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.

[0562] In this invention, the server includes a data receiving means, a regional analysis means, a success case search means, a redevelopment proposal generation means, a financial effect prediction means, an environmental impact assessment means, a long-term impact assessment means, a visual information generation means, and an analysis result display means. This makes it possible to collect and analyze data related to regional redevelopment, present appropriate redevelopment plans, and visually demonstrate their economic effects and environmental impacts.

[0563] A "data receiving means" is a device that has the function of collecting local information provided by the user through their terminal and transferring it to a server.

[0564] A "regional analysis tool" is a tool that has the function of analyzing the current situation and problems of a region based on the received data, and extracting indicators.

[0565] The "success story search method" is a system that uses a generation AI model to search for similar successful redevelopment cases around the world and extracts relevant data.

[0566] A "redevelopment proposal generation tool" is a system that generates redevelopment plans based on regional characteristics and successful case studies, and provides visualized design proposals.

[0567] A "financial effect prediction tool" is a tool that has the function of simulating the economic effects of a proposed redevelopment plan and conducting risk analysis.

[0568] An "environmental impact assessment tool" is a tool that evaluates the environmental impact of a proposed redevelopment plan and has the function of integrating design elements that take sustainability into consideration.

[0569] A "long-term impact assessment tool" is a tool that has the function of evaluating the long-term effects that redevelopment has on local communities and economies.

[0570] A "visual information generation means" is a device that has the function of generating visual data to visually represent redevelopment proposals and their impacts.

[0571] "Analysis result display means" refers to a device that has the function of visually displaying the analyzed results or simulation output to the user.

[0572] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. The system is implemented by users inputting information about the area and buildings from a terminal, which is then processed by a server.

[0573] The server first receives regional information transmitted from terminals using a data receiving device. This information includes location, population dynamics, and the current status of facilities. This data is organized by the server and analyzed by a regional analysis device. The analysis uses historical data to identify indicators of regional population trends and economic activity.

[0574] The success story search mechanism allows the server to utilize a generative AI model to search for similar success stories worldwide and filter them to match the user's needs. The generative AI model uses a database of existing success stories.

[0575] In the redevelopment proposal generation system, the server generates an optimal redevelopment plan based on regional characteristics and successful case studies. This plan is visualized and transmitted to the terminal. Visual information generation is used for visualization, and the plan is proposed as a 3D model.

[0576] Through a financial effect prediction system, the server simulates the economic effects of the redevelopment plan and transmits the results to the terminal via an analysis results display system. At this stage, development costs and expected profits are calculated, and risks are assessed.

[0577] Furthermore, using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Sustainable design elements are considered, and its contribution to long-term regional development is analyzed.

[0578] For example, if a user wants to redevelop a shopping street in a regional city, they can input the location data and current status of the shopping street from their terminal. Based on this information, the server can generate an optimal redevelopment plan and present it as a 3D visual.

[0579] An example of a prompt message is, "Please tell me about appropriate successful case studies and redevelopment plans for local shopping districts."

[0580] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0581] Step 1:

[0582] The user's device inputs information about the region and buildings and sends it to the server via a data receiving device. The input information includes the location of the region, population dynamics, and the current status of the facilities. The server organizes this information and stores it in a database in preparation for the next processing step.

[0583] Step 2:

[0584] The server analyzes the received data using regional analysis tools. The server compares historical data with current information in the database, extracting indicators of population trends and economic activity. The output identifies the current situation in the region and related problems.

[0585] Step 3:

[0586] This system uses a generative AI model to search for successful case studies. The server accesses a database of past successful case studies and searches for similar cases based on the prompt text provided by the user. The prompt text and regional characteristics are used as input, and appropriate successful case studies are selected as output.

[0587] Step 4:

[0588] The redevelopment proposal generation mechanism allows the server to generate redevelopment plans based on regional characteristics and successful case studies. The input consists of regional analysis results and searched successful case studies, and the output is a visualized proposal. Here, a visual information generation mechanism is used to generate a 3D model.

[0589] Step 5:

[0590] This financial impact prediction tool uses a server to simulate the economic effects of a redevelopment plan. Input data includes the redevelopment plan and related financial information. Outputs include development costs, expected benefits, and risk analysis results.

[0591] Step 6:

[0592] Using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Inputs include the redevelopment proposal and related data, and outputs provide environmental impact assessments and long-term socioeconomic effects.

[0593] Step 7:

[0594] The server generates proposals and their evaluation results, which are then transmitted to the user's terminal via an analysis results display device. This allows the user to visually review the details of the redevelopment plan and use this information to help them make a final decision on the redevelopment.

[0595] 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.

[0596] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings, further incorporating an emotion engine that recognizes user emotions. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, long-term impact assessment means, and an emotion engine.

[0597] In the data reception process, the user inputs information about the target area and buildings through a terminal. Data such as location information, resident demographics, and facility status are entered and transmitted to the server by the terminal.

[0598] Regional analysis methods analyze the characteristics and current state of a region based on data received by the server. Population trends and economic conditions are compared with a database to identify current challenges.

[0599] The success story search mechanism uses a generated AI model to search for successful redevelopment cases worldwide. It extracts similar projects and selects the most suitable case for each region.

[0600] In the redevelopment proposal generation system, the server generates redevelopment plans based on regional characteristics and successful case studies. The proposals include design concepts that take into account economic benefits and residents' demands.

[0601] The emotion engine collects user emotion data and incorporates it into redevelopment plans. It adjusts proposals by considering residents' emotional reactions and expectations. This information is extracted from sources such as resident surveys and social media data.

[0602] The financial impact prediction tool uses a server to simulate the economic effects of redevelopment plans. It analyzes the costs, benefits, and risks of each plan and performs an evaluation that incorporates sentiment data.

[0603] Using environmental impact assessment tools, the server evaluates the environmental impact of each redevelopment plan. Sustainable design elements are incorporated, and improvement measures are proposed as needed.

[0604] This long-term impact assessment tool evaluates the long-term impact of the server on local communities and economies. It analyzes the quality of life of residents and the potential for economic development.

[0605] As a concrete example of this system, consider the redevelopment of a shopping street in a regional city. When a user inputs location data and current status of the shopping street, the server identifies the local depopulation challenges and presents similar successful case studies. It generates design proposals and visualizes plans that match the needs of shops and residents. It utilizes an emotion engine to receive feedback from residents and incorporate it into the proposals. As a result, users can select the most suitable redevelopment plan for revitalizing the shopping street and create a plan for its implementation.

[0606] The following describes the processing flow.

[0607] Step 1:

[0608] The user inputs information about the area and buildings targeted for redevelopment into the terminal. Specifically, this includes location information, demographics, and the condition of the buildings. The terminal then organizes this data and prepares it for transmission to the server.

[0609] Step 2:

[0610] The terminal sends the formatted data to the server. The data is structured and sent in a format that is easy for the server to parse.

[0611] Step 3:

[0612] The server receives data and uses regional analysis tools to assess the current state of the region. By referring to historical data, it analyzes demographic trends and changes in economic activity to clarify challenges.

[0613] Step 4:

[0614] The server utilizes a success story search mechanism to search for successful redevelopment cases worldwide using a generating AI model. Similar projects are extracted, and the most suitable case is selected.

[0615] Step 5:

[0616] The server generates redevelopment plans based on regional characteristics and successful case studies using a redevelopment proposal generation system. Multiple design options are proposed, taking into account economic benefits and residents' needs.

[0617] Step 6:

[0618] The server activates the emotion engine and collects user feedback data and public sentiment from relevant information. This information is then used to refine the proposal from an emotional perspective.

[0619] Step 7:

[0620] The server visualizes the redevelopment proposals it generates and sends them to the terminal. The terminal displays the visual design to make it easy for the user to review each proposal.

[0621] Step 8:

[0622] The server uses financial effect prediction tools to simulate the economic impact of each proposal. This includes a cost-benefit analysis for each proposed redevelopment plan.

[0623] Step 9:

[0624] The server will use environmental impact assessment tools to evaluate how the proposed design will affect the environment. Sustainable design elements will be considered, and any areas for improvement will be suggested.

[0625] Step 10:

[0626] The server uses long-term impact assessment tools to evaluate the long-term impact of redevelopment on the region. It analyzes the potential for improving the quality of life for residents and stimulating the economy.

[0627] Step 11:

[0628] Users review analysis results and suggestions sent from the server via their devices and select the optimal redevelopment plan. They then create a plan to implement the redevelopment based on the selected plan.

[0629] (Example 2)

[0630] 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."

[0631] In the redevelopment of sparsely populated areas and aging buildings, there is a need to develop efficient and sustainable plans. Furthermore, it is necessary to create redevelopment projects that appropriately reflect the feelings of residents, thereby improving acceptance and satisfaction within the local community.

[0632] 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.

[0633] In this invention, the server includes means for data input and transmission, means for analyzing regional characteristics and current conditions, means for searching for successful cases using a generative AI model, means for generating redevelopment plans based on regional characteristics and successful cases, means for collecting user sentiment data and reflecting it in the redevelopment plan, means for performing financial simulations of the redevelopment plan, means for evaluating the environmental impact of the redevelopment plan, and means for evaluating the long-term impact on the local community and economy. This makes it possible to formulate efficient, sustainable redevelopment plans that reflect sentiment data.

[0634] "Data input and transmission means" refers to the means by which a user inputs information about a target area or building into a terminal and transmits it to a server.

[0635] "Means for analyzing regional characteristics and current situation" refers to methods for analyzing data in order to understand regional characteristics and recognize current problems.

[0636] "A method for searching for successful cases using a generative AI model" refers to a method of using generative AI to search for successful redevelopment projects from among similar cases.

[0637] "Methods for generating redevelopment plans based on regional characteristics and successful case studies" refers to methods for creating optimal redevelopment plans by combining regional characteristics with past successful case studies.

[0638] "Methods for collecting user emotional data and reflecting it in redevelopment plans" refers to methods for analyzing emotional data obtained from users and utilizing it to improve redevelopment plans.

[0639] "Methods for conducting financial simulations of redevelopment plans" refer to methods for analyzing the economic aspects of redevelopment plans and predicting costs and profits.

[0640] "Means for evaluating the environmental impact of redevelopment plans" refers to means for measuring the environmental impact of each redevelopment plan and ensuring sustainability.

[0641] "Means for assessing the long-term impact on local communities and economies" refers to means of analyzing and providing assessment results for the long-term impact of redevelopment on local communities and economies.

[0642] The following describes embodiments for carrying out this system invention.

[0643] Users input detailed information about the target area and buildings using their devices. This information includes location data, resident demographics, and facility status. The devices transmit this data to a server, which is then used as foundational information for the redevelopment project.

[0644] The server is equipped with hardware for advanced data processing and analyzes regional characteristics and current conditions. This includes identifying challenges in the target region using demographic data and regional economic databases.

[0645] Servers equipped with a generative AI model efficiently search for successful examples of similar redevelopment projects from around the world. The AI ​​model calculates similarity based on the input data and uses prompts to select the most suitable examples.

[0646] Users provide feedback, which is collected on their devices. Emotional data, analyzed through an emotion engine, is reflected in the redevelopment plan. Based on this, the server further refines the redevelopment proposal, creating a plan that meets residents' expectations.

[0647] The server uses financial simulation tools to analyze the costs, benefits, and risks of the redevelopment plan. It also uses environmental impact assessment tools to measure the environmental impact of the redevelopment and construct a sustainable design.

[0648] As a concrete example, when considering the redevelopment of a shopping street in a regional city, the user inputs data on the location and current status of the shopping street. The server analyzes the characteristics of the area, presents successful case studies that can help revitalize the shopping street, and generates design proposals. By utilizing an emotion engine, receiving feedback from residents, and adjusting the proposals, it is possible to create a redevelopment plan that is optimal for revitalizing the shopping street.

[0649] Examples of prompt statements include, "Please provide successful case studies of shopping district redevelopment in regional cities and propose a new plan based on them."

[0650] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0651] Step 1:

[0652] Users input information about the target area and buildings using a terminal. This information includes location data, resident demographics, and facility status. The input data is formatted by the terminal and sent to the server as initial analysis data.

[0653] Step 2:

[0654] The server receives information transmitted from the terminal using a data receiving device. The server then compares the input data with demographic and economic databases to analyze regional characteristics and the current situation. In this process, the server processes the data to identify regional issues and generates analysis results.

[0655] Step 3:

[0656] The server uses a generative AI model to search for similar redevelopment cases. Based on the input data, the AI ​​model performs similarity calculations and extracts appropriate successful cases. A prompt is then used to run the AI ​​model. As a result, a list of the most suitable cases is output.

[0657] Step 4:

[0658] The server generates redevelopment plans based on regional characteristics and successful case studies. The server creates plan prototypes using existing design templates and performs data calculations to reflect economic feasibility and residents' demands. Finally, the proposed plan is generated.

[0659] Step 5:

[0660] Users review initial redevelopment proposals via their devices and provide feedback. This feedback is collected as sentiment data and sent from the device to a server. On the server, a sentiment engine analyzes the data and uses it to refine the proposals.

[0661] Step 6:

[0662] The server performs a financial simulation of the proposed redevelopment plan. It receives details of the proposed plan as input and performs calculations to predict costs, profits, and risks. The resulting financial evaluation is then generated.

[0663] Step 7:

[0664] The server performs environmental impact assessments for each redevelopment plan. It inputs data on environmental burden and sustainability and analyzes it using environmental assessment tools. As output, it provides a report on the degree of environmental impact.

[0665] Step 8:

[0666] The server conducts a long-term impact assessment on the local community and economy. It runs simulations to evaluate the long-term quality of life for residents and the potential for economic growth. The analysis results generate a report on the expected long-term effects.

[0667] (Application Example 2)

[0668] 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."

[0669] In the redevelopment of sparsely populated areas and aging buildings, there is a need to quickly generate and propose effective and sustainable redevelopment plans while taking into account the feelings of local residents. In this situation, conventional methods have difficulty adequately incorporating the feelings of local residents, and the lack of sufficient visualization of redevelopment plans makes it difficult to gain the understanding and cooperation of residents.

[0670] 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.

[0671] In this invention, the server includes data receiving means, regional analysis means, success case search means, sentiment data analysis means, virtual reality visualization means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means. This makes it possible to reflect the sentiments of local residents in the redevelopment plan and visualize it using virtual reality technology, thereby achieving effective and sustainable redevelopment while gaining the understanding and cooperation of residents.

[0672] A "data receiving means" is a mechanism for collecting information about regions and buildings provided by users and receiving it in a format that can be processed within the system.

[0673] A "regional analysis tool" is a function that analyzes the characteristics and problems of a region based on the received data and evaluates the current situation.

[0674] The "success story search tool" is a system for searching and referencing past redevelopment projects around the world that have been successful under similar conditions.

[0675] The "redevelopment proposal generation tool" is a component for formulating the most suitable redevelopment plan for a target area, based on analysis results and successful case studies.

[0676] "Emotional data analysis methods" refer to technologies that analyze emotional data collected from local residents and reflect their opinions and feelings in redevelopment plans.

[0677] A "virtual reality visualization device" is a device that uses virtual reality technology to visually represent the generated redevelopment plan in 3D and present it to the user.

[0678] "Financial impact prediction methods" are techniques for predicting the economic impact of a proposed redevelopment plan and for conducting cost-benefit analyses.

[0679] "Environmental impact assessment tools" are a function that evaluates how a redevelopment plan will affect the local natural environment and ecosystem, and takes sustainability into consideration.

[0680] "Long-term impact assessment methods" are evaluation methods that predict the long-term impacts that redevelopment will have on local communities and economies, with the aim of promoting regional development and improving the quality of life for residents.

[0681] To implement this system, users must first input information about the areas and buildings they wish to redevelop using a device such as a smartphone or computer. This input data is received by a data receiving device on the server. The server uses regional analysis tools to analyze the characteristics and current state of the area, and identifies regional issues based on population composition, economic data, etc.

[0682] Next, the server incorporates a success story search mechanism, which uses a generative AI model to search a database of similar redevelopment projects worldwide. This model extracts successful examples from regions with similar conditions, allowing users to select the most effective redevelopment method.

[0683] Furthermore, emotional data acquired from users is analyzed through an emotional data analysis system. This data is collected from resident surveys and social media and is used to measure users' emotional responses to proposals. Based on the results of this analysis, the server uses a redevelopment proposal generation system to create a redevelopment plan that is tailored to the characteristics of the region and the users.

[0684] Furthermore, virtual reality visualization allows the generated plan to be visualized in 3D, enabling users to view the plan in real time within a virtual reality space. This makes it possible for users to visually understand what the specific proposal means to them.

[0685] Financial impact prediction tools predict the economic impact of the generated plans and analyze the balance between costs and benefits. This analysis also takes into account the risks and benefits of the redevelopment proposals. In addition, environmental impact assessment tools evaluate in detail the environmental impact of each plan and take sustainable design into consideration.

[0686] Finally, long-term impact assessment tools are used to evaluate the long-term impacts of the redevelopment on the local community. This allows for a comprehensive determination of whether the redevelopment will improve the quality of life for residents or contribute to economic development.

[0687] As a concrete example of this system, a shopping district in a local city is taken up. When a user inputs data about the shopping district into the system, the server automatically analyzes the local situation and proposes a redevelopment plan based on past successful cases. This plan is visualized using VR technology and optimized based on feedback from residents' sentiment data.

[0688] An example of a prompt statement is as follows:

[0689] "The goal is to redevelop a shopping street in a sparsely populated area. Please generate the optimal redevelopment plan based on emotional feedback received from users. Location information is entered as ___, and residents' emotions are entered as ___."

[0690] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0691] Step 1:

[0692] Users use a terminal to input information about the area and buildings they wish to redevelop. This includes location information, population demographics, and information about surrounding facilities. This data is then transmitted from the terminal to the server.

[0693] Step 2:

[0694] The server receives information sent by users using a data receiving device. The received data is input into a regional analysis device and used as basic data for analyzing regional characteristics and challenges. Here, it is cross-referenced with databases such as demographic data and economic indicators.

[0695] Step 3:

[0696] The server uses a success story search mechanism and leverages a generative AI model to search the database for past successful redevelopment cases similar to the input regional data. During this process, prompts are used to instruct the AI ​​model on specific data search conditions. As a result of the search, a list of relevant case studies is generated.

[0697] Step 4:

[0698] Based on a list of successful cases, the server generates a redevelopment plan using a redevelopment proposal generation method. Here, a plan is created that considers past successes and regional characteristics, while also meeting economic requirements and the needs of local residents. A generating AI model calculates appropriate design and layout.

[0699] Step 5:

[0700] Users input emotional data using their devices. This data, obtained from resident surveys and social media, reflects the expectations and concerns of local residents regarding the redevelopment plan. This data is then transmitted to a server.

[0701] Step 6:

[0702] The server uses emotional data analysis tools to analyze residents' emotional data and feed it back into the redevelopment plan. Based on the analysis results, the plan is adjusted and optimized to be more acceptable to residents.

[0703] Step 7:

[0704] Through virtual reality visualization, the optimized redevelopment plan is visually presented to the user as a 3D model. The user can then use VR technology to view this visualized plan on their device and confirm the details of the specific proposal.

[0705] Step 8:

[0706] The server uses financial impact forecasting tools to simulate the economic impact of the revised plan. It calculates input costs and projected revenues to assess the project's profitability.

[0707] Step 9:

[0708] Using environmental impact assessment tools, the server analyzes the impact of the redevelopment plan on the local environment. From a sustainability perspective, it modifies the plan if necessary.

[0709] Step 10:

[0710] Using long-term impact assessment tools, the server evaluates the long-term effects of the plan on the local community and economy. It makes a comprehensive judgment on whether it will contribute to local development and improvement of residents' lives.

[0711] 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.

[0712] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0713] 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.

[0714] [Fourth Embodiment]

[0715] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0716] 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.

[0717] 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).

[0718] 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.

[0719] 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.

[0720] 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).

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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".

[0728] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means.

[0729] Regarding the data reception method, users input information about the target area and buildings using a terminal. This information includes, for example, location, population dynamics, and the current status of the facilities. The terminal then compiles this information and sends it to the server.

[0730] In regional analysis, the server uses the received data to analyze the current state of the region. By referring to historical databases, it extracts indicators related to population trends and economic activity, and identifies current problems.

[0731] The success story search mechanism uses a generator AI model to search for successful redevelopment cases around the world. It filters cases similar to regional characteristics and challenges, and provides the relevant data to the user's terminal.

[0732] The redevelopment proposal generation system uses a server to generate an optimal redevelopment plan based on regional characteristics and successful case studies. This proposal includes multiple design options that consider economic effects and residents' needs. The generated design options are visualized and sent to the user's terminal.

[0733] In the financial impact prediction method, the server simulates the economic effects of the proposed redevelopment plan. This includes calculating development costs and expected profits, as well as conducting a risk analysis.

[0734] In environmental impact assessments, the server evaluates the environmental impact of the proposed redevelopment plan. Environmental considerations are taken into account, and sustainable design elements are integrated.

[0735] Long-term impact assessment methods evaluate the long-term effects that servers have on local communities and economies. This involves analyzing the quality of life of residents and the potential for regional revitalization, and considering factors that contribute to future development.

[0736] As an example of this system, consider the process of redeveloping a shopping street in a regional city. When a user inputs location data and current conditions of the shopping street, the server identifies the depopulation problem and provides similar successful case studies. Next, it generates multiple redevelopment plans suitable for the shopping street and visualizes designs tailored to the needs of shops and residents. Furthermore, it simulates the economic effects of each proposal and suggests environmentally conscious designs. Through this process, users can select the appropriate redevelopment plan for revitalizing the shopping street.

[0737] The following describes the processing flow.

[0738] Step 1:

[0739] The user inputs information about the target area or building into the device. This includes location information, current facility status, and demographic data.

[0740] Step 2:

[0741] The terminal processes the input information and sends it to the server as structured data. This involves data format conversion and transfer according to the necessary protocols.

[0742] Step 3:

[0743] The server analyzes the received data and uses regional analysis tools to assess the current situation. It compares this data with past data and cross-references it with databases to identify regional economic conditions and challenges faced by residents.

[0744] Step 4:

[0745] The server uses a generation AI model and a success story search method to find matching redevelopment cases around the world. It extracts similar projects and selects the case that is best suited to the regional characteristics.

[0746] Step 5:

[0747] The server uses a redevelopment proposal generation system to generate multiple redevelopment plans based on regional characteristics and successful case studies. These plans include design proposals that take into account the needs and economic benefits of the residents.

[0748] Step 6:

[0749] The server visualizes the generated proposals and sends them to the terminal. The terminal visually presents each project proposal so that the user can view and compare them.

[0750] Step 7:

[0751] The server uses financial effect prediction tools to simulate the economic impact of the redevelopment plan. For each proposed plan, it performs a cost analysis and calculates the expected profits.

[0752] Step 8:

[0753] The server uses environmental impact assessment tools to evaluate the environmental impact of each redevelopment plan. It verifies whether sustainable design elements are incorporated into the proposal and suggests improvements as needed.

[0754] Step 9:

[0755] The long-term impact of the server on local communities and economies will be evaluated using long-term impact assessment methods. The potential for improving the quality of life for local residents and stimulating the economy will be analyzed.

[0756] Step 10:

[0757] Users receive various reports via their devices and select the most suitable option from several proposed redevelopment plans. Through this process, effective redevelopment aimed at sustainable regional development is carried out.

[0758] (Example 1)

[0759] 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".

[0760] Redeveloping sparsely populated areas and dilapidated buildings presents challenges in formulating appropriate plans tailored to local characteristics. It requires ensuring economic and environmental sustainability while delivering long-term benefits to the local community. However, previous redevelopment projects have struggled to quickly process extensive data and conduct accurate analysis and evaluation, thus failing to derive optimal redevelopment strategies.

[0761] 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.

[0762] In this invention, the server includes means for inputting and transmitting data to the server, means for analyzing the current situation in the region, and means for searching for successful cases using an AI model. This makes it possible to quickly generate optimal redevelopment plans tailored to regional characteristics and provide sustainable redevelopment measures by conducting economic and environmental evaluations.

[0763] "Means of inputting data and sending it to a server" refers to the function of organizing information entered by a user using a terminal and sending it to a server via a network.

[0764] "Means for analyzing the current state of a region" refers to a function where the server uses historical databases to analyze regional population trends and economic indicators, and to identify the current situation and problems.

[0765] "A method for searching for success stories using AI models" refers to a function that uses generative AI models to search for similar success stories from around the world and extract information that matches regional characteristics from among them.

[0766] "Means for generating plans based on regional characteristics and similar cases" refers to the function where the server designs and proposes the optimal redevelopment plan based on identified regional characteristics and successful case studies.

[0767] "A simulation method for predicting the economic effects of a redevelopment plan" refers to a function where the server estimates the economic impact of a proposed redevelopment plan and performs simulations, including risk analysis.

[0768] "Means for evaluating the environmental impact of the plan" refers to the function that allows the server to evaluate the environmental impact of the redevelopment plan and confirm sustainable design elements.

[0769] "Means for evaluating long-term social and economic impacts" refers to the server's ability to analyze and predict the long-term social and economic effects that redevelopment plans will have on the region and its residents.

[0770] This invention is a system for efficiently and sustainably carrying out redevelopment projects in sparsely populated areas and for aging buildings.

[0771] Users input data on the redevelopment area and buildings using a terminal. This data includes the location of the area, population demographics, and the current status of buildings and facilities. Personal computers and tablet devices are used as these terminals, and they are responsible for formatting the data after input and sending it to the server.

[0772] The server interacts with a database to analyze the received data, extracting regional population trends and economic indicators. This process utilizes big data analysis techniques and statistical models. Next, a generative AI model is used to search for similar success stories based on a prompt (e.g., "Please provide examples of successful redevelopment in depopulated areas"). Information on these success stories is retrieved from a data repository in the cloud.

[0773] Subsequently, the server generates multiple redevelopment plans based on regional characteristics and successful case studies. This includes visualizing the designs using specialized CAD software. The generated designs are then subjected to cost-benefit analysis using economic simulations. These simulations include calculations of development costs and expected profits. Furthermore, environmental assessment tools are used to ensure that the redevelopment plans are sustainable for the local community and the environment.

[0774] A concrete example is a redevelopment project for a shopping district in a regional city. When a user inputs location data and current conditions of the shopping district, the server identifies the problem of depopulation and provides similar successful case studies. Furthermore, it generates multiple redevelopment plans tailored to the shopping district, presenting designs that reflect the needs of shop owners and residents. Through simulation and evaluation, it is possible to propose an optimal, environmentally conscious redevelopment plan.

[0775] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0776] Step 1:

[0777] The user uses a terminal to input data such as the redevelopment area, building locations, population dynamics, and the current status of facilities. The terminal formats the input data in the appropriate format. It verifies the input data to ensure there are no errors. After the data is formatted, the terminal sends this information to the server via the network.

[0778] Step 2:

[0779] The server stores the received data and analyzes the current situation in the region. The server references the database to extract historical population trends and indicators of economic activity. It also applies statistical models to identify current problems based on the data. The input is regional data received from the user, and the output is a detailed report on the region where problems have been identified.

[0780] Step 3:

[0781] The server runs a generative AI model and searches for similar success stories worldwide using the prompt "Please show me successful examples of redevelopment in sparsely populated areas." The AI ​​model filters the results to select examples that are similar to the characteristics of the region. The input is the result of the regional analysis, and the output is a list of information about the success stories.

[0782] Step 4:

[0783] The server creates a redevelopment plan using a redevelopment proposal generation method based on similar cases. Multiple design options are visualized using CAD software and sent to the user's terminal. The input is data from successful cases, and the output is a visualized redevelopment plan.

[0784] Step 5:

[0785] The server performs simulations to predict the economic impact of a redevelopment plan. It calculates development costs and expected profits, and conducts risk analysis. As a result, it generates a financial indicators report and provides it to the user. The input is the redevelopment plan, and the output is a report predicting the economic impact.

[0786] Step 6:

[0787] The server analyzes the environmental impact of the redevelopment proposal using environmental impact assessment tools. It verifies whether the redevelopment plan includes sustainable design elements and adjusts the design as necessary. The input is the redevelopment plan, and the output is the results of the environmental impact assessment.

[0788] Step 7:

[0789] The server evaluates the long-term effects of a redevelopment plan on the local community and economy. It analyzes the potential for improving residents' quality of life and revitalizing the area, and ultimately provides users with proposals that consider factors contributing to future development. The input is the redevelopment plan, and the output is the result of the long-term impact assessment.

[0790] (Application Example 1)

[0791] 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".

[0792] One challenge is the difficulty in developing concrete plans for the efficient and sustainable redevelopment of areas and buildings facing depopulation and aging infrastructure. Furthermore, there is the difficulty in visually demonstrating the effects and impacts of redevelopment, making it challenging to gain the understanding of stakeholders.

[0793] 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.

[0794] In this invention, the server includes a data receiving means, a regional analysis means, a success case search means, a redevelopment proposal generation means, a financial effect prediction means, an environmental impact assessment means, a long-term impact assessment means, a visual information generation means, and an analysis result display means. This makes it possible to collect and analyze data related to regional redevelopment, present appropriate redevelopment plans, and visually demonstrate their economic effects and environmental impacts.

[0795] A "data receiving means" is a device that has the function of collecting local information provided by the user through their terminal and transferring it to a server.

[0796] A "regional analysis tool" is a tool that has the function of analyzing the current situation and problems of a region based on the received data, and extracting indicators.

[0797] The "success story search method" is a system that uses a generation AI model to search for similar successful redevelopment cases around the world and extracts relevant data.

[0798] A "redevelopment proposal generation tool" is a system that generates redevelopment plans based on regional characteristics and successful case studies, and provides visualized design proposals.

[0799] A "financial effect prediction tool" is a tool that has the function of simulating the economic effects of a proposed redevelopment plan and conducting risk analysis.

[0800] An "environmental impact assessment tool" is a tool that evaluates the environmental impact of a proposed redevelopment plan and has the function of integrating design elements that take sustainability into consideration.

[0801] A "long-term impact assessment tool" is a tool that has the function of evaluating the long-term effects that redevelopment has on local communities and economies.

[0802] A "visual information generation means" is a device that has the function of generating visual data to visually represent redevelopment proposals and their impacts.

[0803] "Analysis result display means" refers to a device that has the function of visually displaying the analyzed results or simulation output to the user.

[0804] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings. The system is implemented by users inputting information about the area and buildings from a terminal, which is then processed by a server.

[0805] The server first receives regional information transmitted from terminals using a data receiving device. This information includes location, population dynamics, and the current status of facilities. This data is organized by the server and analyzed by a regional analysis device. The analysis uses historical data to identify indicators of regional population trends and economic activity.

[0806] The success story search mechanism allows the server to utilize a generative AI model to search for similar success stories worldwide and filter them to match the user's needs. The generative AI model uses a database of existing success stories.

[0807] In the redevelopment proposal generation system, the server generates an optimal redevelopment plan based on regional characteristics and successful case studies. This plan is visualized and transmitted to the terminal. Visual information generation is used for visualization, and the plan is proposed as a 3D model.

[0808] Through a financial effect prediction system, the server simulates the economic effects of the redevelopment plan and transmits the results to the terminal via an analysis results display system. At this stage, development costs and expected profits are calculated, and risks are assessed.

[0809] Furthermore, using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Sustainable design elements are considered, and its contribution to long-term regional development is analyzed.

[0810] For example, if a user wants to redevelop a shopping street in a regional city, they can input the location data and current status of the shopping street from their terminal. Based on this information, the server can generate an optimal redevelopment plan and present it as a 3D visual.

[0811] An example of a prompt message is, "Please tell me about appropriate successful case studies and redevelopment plans for local shopping districts."

[0812] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0813] Step 1:

[0814] The user's device inputs information about the region and buildings and sends it to the server via a data receiving device. The input information includes the location of the region, population dynamics, and the current status of the facilities. The server organizes this information and stores it in a database in preparation for the next processing step.

[0815] Step 2:

[0816] The server analyzes the received data using regional analysis tools. The server compares historical data with current information in the database, extracting indicators of population trends and economic activity. The output identifies the current situation in the region and related problems.

[0817] Step 3:

[0818] This system uses a generative AI model to search for successful case studies. The server accesses a database of past successful case studies and searches for similar cases based on the prompt text provided by the user. The prompt text and regional characteristics are used as input, and appropriate successful case studies are selected as output.

[0819] Step 4:

[0820] The redevelopment proposal generation mechanism allows the server to generate redevelopment plans based on regional characteristics and successful case studies. The input consists of regional analysis results and searched successful case studies, and the output is a visualized proposal. Here, a visual information generation mechanism is used to generate a 3D model.

[0821] Step 5:

[0822] This financial impact prediction tool uses a server to simulate the economic effects of a redevelopment plan. Input data includes the redevelopment plan and related financial information. Outputs include development costs, expected benefits, and risk analysis results.

[0823] Step 6:

[0824] Using environmental impact assessment tools and long-term impact assessment tools, the server evaluates the environmental and socioeconomic impacts of the proposed plan. Inputs include the redevelopment proposal and related data, and outputs provide environmental impact assessments and long-term socioeconomic effects.

[0825] Step 7:

[0826] The server generates proposals and their evaluation results, which are then transmitted to the user's terminal via an analysis results display device. This allows the user to visually review the details of the redevelopment plan and use this information to help them make a final decision on the redevelopment.

[0827] 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.

[0828] This invention provides a system for efficiently and sustainably redeveloping sparsely populated areas and dilapidated buildings, further incorporating an emotion engine that recognizes user emotions. This system includes data receiving means, regional analysis means, success case search means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, long-term impact assessment means, and an emotion engine.

[0829] In the data reception process, the user inputs information about the target area and buildings through a terminal. Data such as location information, resident demographics, and facility status are entered and transmitted to the server by the terminal.

[0830] Regional analysis methods analyze the characteristics and current state of a region based on data received by the server. Population trends and economic conditions are compared with a database to identify current challenges.

[0831] The success story search mechanism uses a generated AI model to search for successful redevelopment cases worldwide. It extracts similar projects and selects the most suitable case for each region.

[0832] In the redevelopment proposal generation system, the server generates redevelopment plans based on regional characteristics and successful case studies. The proposals include design concepts that take into account economic benefits and residents' demands.

[0833] The emotion engine collects user emotion data and incorporates it into redevelopment plans. It adjusts proposals by considering residents' emotional reactions and expectations. This information is extracted from sources such as resident surveys and social media data.

[0834] The financial impact prediction tool uses a server to simulate the economic effects of redevelopment plans. It analyzes the costs, benefits, and risks of each plan and performs an evaluation that incorporates sentiment data.

[0835] Using environmental impact assessment tools, the server evaluates the environmental impact of each redevelopment plan. Sustainable design elements are incorporated, and improvement measures are proposed as needed.

[0836] This long-term impact assessment tool evaluates the long-term impact of the server on local communities and economies. It analyzes the quality of life of residents and the potential for economic development.

[0837] As a concrete example of this system, consider the redevelopment of a shopping street in a regional city. When a user inputs location data and current status of the shopping street, the server identifies the local depopulation challenges and presents similar successful case studies. It generates design proposals and visualizes plans that match the needs of shops and residents. It utilizes an emotion engine to receive feedback from residents and incorporate it into the proposals. As a result, users can select the most suitable redevelopment plan for revitalizing the shopping street and create a plan for its implementation.

[0838] The following describes the processing flow.

[0839] Step 1:

[0840] The user inputs information about the area and buildings targeted for redevelopment into the terminal. Specifically, this includes location information, demographics, and the condition of the buildings. The terminal then organizes this data and prepares it for transmission to the server.

[0841] Step 2:

[0842] The terminal sends the formatted data to the server. The data is structured and sent in a format that is easy for the server to parse.

[0843] Step 3:

[0844] The server receives data and uses regional analysis tools to assess the current state of the region. By referring to historical data, it analyzes demographic trends and changes in economic activity to clarify challenges.

[0845] Step 4:

[0846] The server utilizes a success story search mechanism to search for successful redevelopment cases worldwide using a generating AI model. Similar projects are extracted, and the most suitable case is selected.

[0847] Step 5:

[0848] The server generates redevelopment plans based on regional characteristics and successful case studies using a redevelopment proposal generation system. Multiple design options are proposed, taking into account economic benefits and residents' needs.

[0849] Step 6:

[0850] The server activates the emotion engine and collects user feedback data and public sentiment from relevant information. This information is then used to refine the proposal from an emotional perspective.

[0851] Step 7:

[0852] The server visualizes the redevelopment proposals it generates and sends them to the terminal. The terminal displays the visual design to make it easy for the user to review each proposal.

[0853] Step 8:

[0854] The server uses financial effect prediction tools to simulate the economic impact of each proposal. This includes a cost-benefit analysis for each proposed redevelopment plan.

[0855] Step 9:

[0856] The server will use environmental impact assessment tools to evaluate how the proposed design will affect the environment. Sustainable design elements will be considered, and any areas for improvement will be suggested.

[0857] Step 10:

[0858] The server uses long-term impact assessment tools to evaluate the long-term impact of redevelopment on the region. It analyzes the potential for improving the quality of life for residents and stimulating the economy.

[0859] Step 11:

[0860] Users review analysis results and suggestions sent from the server via their devices and select the optimal redevelopment plan. They then create a plan to implement the redevelopment based on the selected plan.

[0861] (Example 2)

[0862] 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".

[0863] In the redevelopment of sparsely populated areas and aging buildings, there is a need to develop efficient and sustainable plans. Furthermore, it is necessary to create redevelopment projects that appropriately reflect the feelings of residents, thereby improving acceptance and satisfaction within the local community.

[0864] 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.

[0865] In this invention, the server includes means for data input and transmission, means for analyzing regional characteristics and current conditions, means for searching for successful cases using a generative AI model, means for generating redevelopment plans based on regional characteristics and successful cases, means for collecting user sentiment data and reflecting it in the redevelopment plan, means for performing financial simulations of the redevelopment plan, means for evaluating the environmental impact of the redevelopment plan, and means for evaluating the long-term impact on the local community and economy. This makes it possible to formulate efficient, sustainable redevelopment plans that reflect sentiment data.

[0866] "Data input and transmission means" refers to the means by which a user inputs information about a target area or building into a terminal and transmits it to a server.

[0867] "Means for analyzing regional characteristics and current situation" refers to methods for analyzing data in order to understand regional characteristics and recognize current problems.

[0868] "A method for searching for successful cases using a generative AI model" refers to a method of using generative AI to search for successful redevelopment projects from among similar cases.

[0869] "Methods for generating redevelopment plans based on regional characteristics and successful case studies" refers to methods for creating optimal redevelopment plans by combining regional characteristics with past successful case studies.

[0870] "Methods for collecting user emotional data and reflecting it in redevelopment plans" refers to methods for analyzing emotional data obtained from users and utilizing it to improve redevelopment plans.

[0871] "Methods for conducting financial simulations of redevelopment plans" refer to methods for analyzing the economic aspects of redevelopment plans and predicting costs and profits.

[0872] "Means for evaluating the environmental impact of redevelopment plans" refers to means for measuring the environmental impact of each redevelopment plan and ensuring sustainability.

[0873] "Means for assessing the long-term impact on local communities and economies" refers to means of analyzing and providing assessment results for the long-term impact of redevelopment on local communities and economies.

[0874] The following describes embodiments for carrying out this system invention.

[0875] Users input detailed information about the target area and buildings using their devices. This information includes location data, resident demographics, and facility status. The devices transmit this data to a server, which is then used as foundational information for the redevelopment project.

[0876] The server is equipped with hardware for advanced data processing and analyzes regional characteristics and current conditions. This includes identifying challenges in the target region using demographic data and regional economic databases.

[0877] Servers equipped with a generative AI model efficiently search for successful examples of similar redevelopment projects from around the world. The AI ​​model calculates similarity based on the input data and uses prompts to select the most suitable examples.

[0878] Users provide feedback, which is collected on their devices. Emotional data, analyzed through an emotion engine, is reflected in the redevelopment plan. Based on this, the server further refines the redevelopment proposal, creating a plan that meets residents' expectations.

[0879] The server uses financial simulation tools to analyze the costs, benefits, and risks of the redevelopment plan. It also uses environmental impact assessment tools to measure the environmental impact of the redevelopment and construct a sustainable design.

[0880] As a concrete example, when considering the redevelopment of a shopping street in a regional city, the user inputs data on the location and current status of the shopping street. The server analyzes the characteristics of the area, presents successful case studies that can help revitalize the shopping street, and generates design proposals. By utilizing an emotion engine, receiving feedback from residents, and adjusting the proposals, it is possible to create a redevelopment plan that is optimal for revitalizing the shopping street.

[0881] Examples of prompt statements include, "Please provide successful case studies of shopping district redevelopment in regional cities and propose a new plan based on them."

[0882] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0883] Step 1:

[0884] Users input information about the target area and buildings using a terminal. This information includes location data, resident demographics, and facility status. The input data is formatted by the terminal and sent to the server as initial analysis data.

[0885] Step 2:

[0886] The server receives information transmitted from the terminal using a data receiving device. The server then compares the input data with demographic and economic databases to analyze regional characteristics and the current situation. In this process, the server processes the data to identify regional issues and generates analysis results.

[0887] Step 3:

[0888] The server uses a generative AI model to search for similar redevelopment cases. Based on the input data, the AI ​​model performs similarity calculations and extracts appropriate successful cases. A prompt is then used to run the AI ​​model. As a result, a list of the most suitable cases is output.

[0889] Step 4:

[0890] The server generates redevelopment plans based on regional characteristics and successful case studies. The server creates plan prototypes using existing design templates and performs data calculations to reflect economic feasibility and residents' demands. Finally, the proposed plan is generated.

[0891] Step 5:

[0892] Users review initial redevelopment proposals via their devices and provide feedback. This feedback is collected as sentiment data and sent from the device to a server. On the server, a sentiment engine analyzes the data and uses it to refine the proposals.

[0893] Step 6:

[0894] The server performs a financial simulation of the proposed redevelopment plan. It receives details of the proposed plan as input and performs calculations to predict costs, profits, and risks. The resulting financial evaluation is then generated.

[0895] Step 7:

[0896] The server performs environmental impact assessments for each redevelopment plan. It inputs data on environmental burden and sustainability and analyzes it using environmental assessment tools. As output, it provides a report on the degree of environmental impact.

[0897] Step 8:

[0898] The server conducts a long-term impact assessment on the local community and economy. It runs simulations to evaluate the long-term quality of life for residents and the potential for economic growth. The analysis results generate a report on the expected long-term effects.

[0899] (Application Example 2)

[0900] 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".

[0901] In the redevelopment of sparsely populated areas and aging buildings, there is a need to quickly generate and propose effective and sustainable redevelopment plans while taking into account the feelings of local residents. In this situation, conventional methods have difficulty adequately incorporating the feelings of local residents, and the lack of sufficient visualization of redevelopment plans makes it difficult to gain the understanding and cooperation of residents.

[0902] 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.

[0903] In this invention, the server includes data receiving means, regional analysis means, success case search means, sentiment data analysis means, virtual reality visualization means, redevelopment proposal generation means, financial effect prediction means, environmental impact assessment means, and long-term impact assessment means. This makes it possible to reflect the sentiments of local residents in the redevelopment plan and visualize it using virtual reality technology, thereby achieving effective and sustainable redevelopment while gaining the understanding and cooperation of residents.

[0904] A "data receiving means" is a mechanism for collecting information about regions and buildings provided by users and receiving it in a format that can be processed within the system.

[0905] A "regional analysis tool" is a function that analyzes the characteristics and problems of a region based on the received data and evaluates the current situation.

[0906] The "success story search tool" is a system for searching and referencing past redevelopment projects around the world that have been successful under similar conditions.

[0907] The "redevelopment proposal generation tool" is a component for formulating the most suitable redevelopment plan for a target area, based on analysis results and successful case studies.

[0908] "Emotional data analysis methods" refer to technologies that analyze emotional data collected from local residents and reflect their opinions and feelings in redevelopment plans.

[0909] A "virtual reality visualization device" is a device that uses virtual reality technology to visually represent the generated redevelopment plan in 3D and present it to the user.

[0910] "Financial impact prediction methods" are techniques for predicting the economic impact of a proposed redevelopment plan and for conducting cost-benefit analyses.

[0911] "Environmental impact assessment tools" are a function that evaluates how a redevelopment plan will affect the local natural environment and ecosystem, and takes sustainability into consideration.

[0912] "Long-term impact assessment methods" are evaluation methods that predict the long-term impacts that redevelopment will have on local communities and economies, with the aim of promoting regional development and improving the quality of life for residents.

[0913] To implement this system, users must first input information about the areas and buildings they wish to redevelop using a device such as a smartphone or computer. This input data is received by a data receiving device on the server. The server uses regional analysis tools to analyze the characteristics and current state of the area, and identifies regional issues based on population composition, economic data, etc.

[0914] Next, the server incorporates a success story search mechanism, which uses a generative AI model to search a database of similar redevelopment projects worldwide. This model extracts successful examples from regions with similar conditions, allowing users to select the most effective redevelopment method.

[0915] Furthermore, emotional data acquired from users is analyzed through an emotional data analysis system. This data is collected from resident surveys and social media and is used to measure users' emotional responses to proposals. Based on the results of this analysis, the server uses a redevelopment proposal generation system to create a redevelopment plan that is tailored to the characteristics of the region and the users.

[0916] Furthermore, virtual reality visualization allows the generated plan to be visualized in 3D, enabling users to view the plan in real time within a virtual reality space. This makes it possible for users to visually understand what the specific proposal means to them.

[0917] Financial impact prediction tools predict the economic impact of the generated plans and analyze the balance between costs and benefits. This analysis also takes into account the risks and benefits of the redevelopment proposals. In addition, environmental impact assessment tools evaluate in detail the environmental impact of each plan and take sustainable design into consideration.

[0918] Finally, long-term impact assessment tools are used to evaluate the long-term impacts of the redevelopment on the local community. This allows for a comprehensive determination of whether the redevelopment will improve the quality of life for residents or contribute to economic development.

[0919] As a concrete example of this system, a shopping district in a local city is taken up. When a user inputs data about the shopping district into the system, the server automatically analyzes the local situation and proposes a redevelopment plan based on past successful cases. This plan is visualized using VR technology and optimized based on feedback from residents' sentiment data.

[0920] An example of a prompt statement is as follows:

[0921] "The goal is to redevelop a shopping street in a sparsely populated area. Please generate the optimal redevelopment plan based on emotional feedback received from users. Location information is entered as ___, and residents' emotions are entered as ___."

[0922] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0923] Step 1:

[0924] Users use a terminal to input information about the area and buildings they wish to redevelop. This includes location information, population demographics, and information about surrounding facilities. This data is then transmitted from the terminal to the server.

[0925] Step 2:

[0926] The server receives information sent by users using a data receiving device. The received data is input into a regional analysis device and used as basic data for analyzing regional characteristics and challenges. Here, it is cross-referenced with databases such as demographic data and economic indicators.

[0927] Step 3:

[0928] The server uses a success story search mechanism and leverages a generative AI model to search the database for past successful redevelopment cases similar to the input regional data. During this process, prompts are used to instruct the AI ​​model on specific data search conditions. As a result of the search, a list of relevant case studies is generated.

[0929] Step 4:

[0930] Based on a list of successful cases, the server generates a redevelopment plan using a redevelopment proposal generation method. Here, a plan is created that considers past successes and regional characteristics, while also meeting economic requirements and the needs of local residents. A generating AI model calculates appropriate design and layout.

[0931] Step 5:

[0932] Users input emotional data using their devices. This data, obtained from resident surveys and social media, reflects the expectations and concerns of local residents regarding the redevelopment plan. This data is then transmitted to a server.

[0933] Step 6:

[0934] The server uses emotional data analysis tools to analyze residents' emotional data and feed it back into the redevelopment plan. Based on the analysis results, the plan is adjusted and optimized to be more acceptable to residents.

[0935] Step 7:

[0936] Through virtual reality visualization, the optimized redevelopment plan is visually presented to the user as a 3D model. The user can then use VR technology to view this visualized plan on their device and confirm the details of the specific proposal.

[0937] Step 8:

[0938] The server uses financial impact forecasting tools to simulate the economic impact of the revised plan. It calculates input costs and projected revenues to assess the project's profitability.

[0939] Step 9:

[0940] Using environmental impact assessment tools, the server analyzes the impact of the redevelopment plan on the local environment. From a sustainability perspective, it modifies the plan if necessary.

[0941] Step 10:

[0942] Using long-term impact assessment tools, the server evaluates the long-term effects of the plan on the local community and economy. It makes a comprehensive judgment on whether it will contribute to local development and improvement of residents' lives.

[0943] 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.

[0944] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0945] 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.

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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."

[0952] 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.

[0953] 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.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] 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.

[0958] 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.

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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.

[0963] 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.

[0964] The following is further disclosed regarding the embodiments described above.

[0965] (Claim 1)

[0966] Data receiving means,

[0967] Regional analysis methods,

[0968] Methods for searching for success stories,

[0969] A means for generating redevelopment proposals,

[0970] Financial effect prediction tools,

[0971] Environmental impact assessment methods,

[0972] Long-term impact assessment tools,

[0973] A system that includes this.

[0974] (Claim 2)

[0975] The system according to claim 1, which generates redevelopment plans tailored to regional characteristics.

[0976] (Claim 3)

[0977] The system according to claim 1 for simulating the economic effects of a redevelopment plan.

[0978] "Example 1"

[0979] (Claim 1)

[0980] A means of inputting data and sending it to a server,

[0981] Methods for analyzing the current situation in the region,

[0982] A method for searching for success stories using AI models,

[0983] A means of generating plans based on regional characteristics and similar cases,

[0984] A simulation method for predicting the economic effects of a redevelopment plan,

[0985] Methods for evaluating the environmental impact of the plan,

[0986] A means of assessing the long-term social and economic impacts,

[0987] A system that includes this.

[0988] (Claim 2)

[0989] The system according to claim 1, which generates and visualizes redevelopment plans based on regional characteristics and similar successful cases.

[0990] (Claim 3)

[0991] The system according to claim 1 for evaluating whether a redevelopment plan design takes sustainability into consideration.

[0992] "Application Example 1"

[0993] (Claim 1)

[0994] Data receiving means,

[0995] Regional analysis methods,

[0996] Methods for searching for success stories,

[0997] A means for generating redevelopment proposals,

[0998] Financial effect prediction tools,

[0999] Environmental impact assessment methods,

[1000] Long-term impact assessment tools,

[1001] means for generating visual information,

[1002] means for displaying analysis results,

[1003] A system that includes this.

[1004] (Claim 2)

[1005] The system according to claim 1, which generates and visualizes redevelopment plans tailored to regional characteristics.

[1006] (Claim 3)

[1007] The system according to claim 1, which simulates the economic effects of a redevelopment plan and visualizes the results.

[1008] "Example 2 of combining an emotion engine"

[1009] (Claim 1)

[1010] Data input and transmission means,

[1011] Means for analyzing regional characteristics and current situation,

[1012] A method for searching for successful cases using a generative AI model,

[1013] A means of generating redevelopment plans based on regional characteristics and successful case studies,

[1014] A means of collecting user sentiment data and reflecting it in the redevelopment plan,

[1015] Methods for conducting financial simulations of redevelopment plans,

[1016] Methods for evaluating the environmental impact of redevelopment plans,

[1017] A means of assessing the long-term impact on local communities and economies,

[1018] A system that includes this.

[1019] (Claim 2)

[1020] The system according to claim 1, which generates redevelopment plans tailored to regional characteristics and takes user sentiment data into consideration.

[1021] (Claim 3)

[1022] The system according to claim 1, which simulates the economic effects of a redevelopment plan and performs an evaluation that takes emotional data into account.

[1023] "Application example 2 when combining with an emotional engine"

[1024] (Claim 1)

[1025] Data receiving means,

[1026] Regional analysis methods,

[1027] Methods for searching for success stories,

[1028] A means for generating redevelopment proposals,

[1029] Emotional data analysis methods,

[1030] Virtual reality visualization means,

[1031] Financial effect prediction tools,

[1032] Environmental impact assessment methods,

[1033] Long-term impact assessment tools,

[1034] A system that includes this.

[1035] (Claim 2)

[1036] The system according to claim 1, which generates a redevelopment plan based on regional characteristics and sentiment data.

[1037] (Claim 3)

[1038] The system according to claim 1, which simulates the economic effects of a redevelopment plan using emotional data. [Explanation of symbols]

[1039] 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 data receiving means for acquiring information about regions and buildings provided by the user, A regional analysis method that evaluates the current situation and characteristics of the target area based on the acquired data, A success story search tool that extracts effective redevelopment success stories from around the world and finds similar examples tailored to regional characteristics, A redevelopment proposal generation method that automatically generates multiple redevelopment design plans based on regional characteristics and successful case studies, A financial effect forecasting method that simulates the economic impact of the proposed redevelopment plan and predicts costs and benefits, An environmental impact assessment method that evaluates the potential impact of a redevelopment plan on the local environment and considers sustainable design elements, A long-term impact assessment tool that analyzes the long-term impact of redevelopment plans on local communities and economies and evaluates future development potential, A system that includes this.

2. The system according to claim 1, which generates a redevelopment plan tailored to regional characteristics.

3. The system according to claim 1 for simulating the economic effects of a redevelopment plan.

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