system

Abstract

We provide a system that integrates and manages survey data, behavioral data, and social media data collected from residents, and analyzes them. [Solution] A system comprising: means for managing questionnaire data collected from residents; means for connecting to sensors for collecting residents' behavioral data; means for collecting social media data to which residents have consented; means for analyzing this data and generating residents' digital profiles; means for generating avatars that mimic the residents' thought patterns based on the generated digital profiles; means for executing simulations in which the avatars operate on a digital twin; means for analyzing the simulation results and generating urban planning information; and means for providing local currency as an incentive based on the data provided by residents.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, it is important to accurately capture the needs and opinions of residents in urban planning. However, there is a problem that it is difficult to efficiently aggregate various opinions of residents by conventional methods. Also, since the incentives for obtaining residents' cooperation are not clear, there is a problem that sufficient data collection cannot be achieved. As a result, there is a risk that urban planning cannot reflect the actual needs of residents and leads to insufficient plans.

Means for Solving the Problems

[0005] This invention provides a system for comprehensively managing and analyzing survey data, behavioral data, and social media data collected from residents. Specifically, it generates avatars that mimic residents' thought patterns using digital profiles created from this data. Then, it runs simulations on a digital twin, analyzes the results, and derives information necessary for urban planning. Furthermore, it has a function to provide local currency as an incentive based on the data provided by residents, thereby promoting resident cooperation and data provision. As a result, it enables the formulation of highly accurate urban plans and aims to realize effective plans that reflect the needs of residents.

[0006] "Residents" refer to individuals who live in the city targeted by the system and who cooperate in providing data.

[0007] "Survey data" refers to information obtained from questionnaires answered by residents, and includes individual opinions and wishes.

[0008] "Behavioral data" refers to information about residents' daily movements and habits, which is automatically collected by sensors.

[0009] "Social media data" refers to information obtained from residents' statements and activities on social media, only if they have given their permission.

[0010] A "digital profile" is electronic personal information compiled by analyzing and integrating multiple data points collected from residents.

[0011] An "avatar" is a virtual entity created based on a digital profile that mimics the thought patterns and behavioral characteristics of the residents.

[0012] A "digital twin" is a model that recreates a real city in a virtual space, and serves as the foundation for simulations.

[0013] A "simulation" is a virtual experiment conducted using avatars on a digital twin, and is used to verify the effectiveness of urban planning.

[0014] A "local currency" is a currency usable within a limited area, which is given as compensation for residents providing their data. [Brief explanation of the drawing]

[0015] [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]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the labeled 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), etc.

[0019] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is a system for formulating highly accurate urban plans using resident data, and includes the following functions.

[0037] First, a questionnaire is presented to residents via a device. Users answer the questions presented through the device, and these answers are sent from the device to the server. At this stage, data regarding residents' personal opinions and wishes is collected.

[0038] Next, IoT sensors are used to automatically acquire data on residents' daily activities. The acquired activity data is transferred to a server via a terminal. During this process, location information and residents' movements at specific times are recorded.

[0039] Furthermore, the server collects social media data to the extent permitted by the residents. This is done via the APIs of social media platforms, making it possible to obtain residents' public statements and activity history.

[0040] This data is integrated and analyzed on a server to generate digital profiles of residents. These digital profiles reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars. These avatars mimic the residents' thoughts and behaviors and are used in simulations on the digital twin.

[0041] A digital twin is a virtual environment that recreates a real city in a virtual space, and is used to run simulations using avatars. The server evaluates the effectiveness of urban planning proposals through simulations, analyzes the obtained data, and derives the optimal urban design.

[0042] In this process, residents are offered local currency as a reward for cooperating by providing data. The server calculates the local currency based on the data provided and adds it to the user's account. The terminal displays a notification to the user that they have received the local currency, playing a role in encouraging residents to provide further data.

[0043] For example, when considering the establishment of a new park in a city, the server analyzes resident movement data and survey results, and runs a simulation of the park's placement on a digital twin. Based on these results, it becomes possible to concretely understand the social value and impact that the park would bring and to formulate an appropriate plan.

[0044] Thus, the present invention provides a system that makes it possible to improve the accuracy of urban planning through resident-participatory data collection and analysis.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The terminal presents a questionnaire to the resident. The user answers the questions on the terminal and presses the submit button upon completion. The terminal then sends the collected response data to the server.

[0048] Step 2:

[0049] IoT sensors automatically detect residents' location and activity information. The device receives this data from the sensor and transfers it to the server.

[0050] Step 3:

[0051] The server collects relevant information through social media APIs that residents have previously authorized. The server stores the collected data in an internal database.

[0052] Step 4:

[0053] The server integrates and analyzes survey data, behavioral data, and social media data. Using this data, the server generates digital profiles of residents.

[0054] Step 5:

[0055] Based on the generated digital profile, the server uses a generator AI to create an avatar that possesses the residents' thought patterns and behavioral characteristics.

[0056] Step 6:

[0057] The server runs simulations using avatars on a digital twin. Through these simulations, the server evaluates the effectiveness of proposed urban planning solutions.

[0058] Step 7:

[0059] The server analyzes the simulation results and generates information necessary for urban planning. This generated information is then compiled into a resource that helps improve urban planning.

[0060] Step 8:

[0061] The server calculates the amount of local currency that should be awarded to each user based on the data provided.

[0062] Step 9:

[0063] The server assigns the calculated local currency to the user's account. The terminal displays a notification to the user regarding the received local currency.

[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] In modern urban development, there is a need to reflect the diverse opinions of residents and formulate precise regional plans. However, traditional methods fail to adequately model residents' activities and ideas, making it difficult to create urban plans that reflect their actual lifestyles. Furthermore, there is insufficient incentive provision for residents, and mechanisms to elicit cooperation in providing data are lacking.

[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 managing opinion data collected from residents, means for connecting to a detection device for collecting residents' behavioral data, and means for collecting publicly available data to which residents have consented. This makes it possible to formulate precise regional plans that reflect the thinking patterns of residents.

[0069] "Residents" refers to individuals or groups living in a city or region, and are the providers of survey responses and behavioral data.

[0070] "Opinion data" refers to information about the thoughts and wishes expressed by residents through surveys and feedback.

[0071] "Behavioral data" refers to information about residents' daily movements and activities, and is acquired by detection devices.

[0072] A "detection device" refers to hardware used to sense residents' behavior and the environment and collect data.

[0073] "Public data" refers to information about statements and activity history that residents have made public on social media, etc.

[0074] "Digital information" refers to digitized profiles of residents generated by analyzing their opinion data, behavioral data, and publicly available data.

[0075] "Virtual representation" refers to digital characters and models generated based on the digital information of residents.

[0076] A "virtual environment" refers to a 3D or simulated space created on a computer, and is used in urban planning simulations.

[0077] "Simulation" is a process of conducting experiments using virtual representations within a virtual environment to evaluate the effectiveness of urban planning.

[0078] "Rewards" refer to local currency or perks given as incentives to residents for the data they provide.

[0079] A "local currency" is a unique currency that can be used within a specific region and is given to residents as a reward.

[0080] This invention is a system for formulating sophisticated urban development plans with the participation of residents. An embodiment of this system is described below.

[0081] This system first presents residents with a questionnaire via a terminal. The terminal has a graphical user interface (GUI) and provides a screen that is easy for residents to operate. Users can answer the presented questions using this terminal. This response data is securely transmitted to the server using encryption technology.

[0082] Next, the system utilizes IoT sensors to collect data on residents' daily activities. This consists of GPS modules for acquiring location information and motion sensors for detecting specific activities. The collected data is transmitted to a server via the terminal. The server integrates and centrally manages this data in a cloud environment.

[0083] Furthermore, the server will only collect residents' public statements and activity history through social media APIs if the residents consent. Access control will be implemented during this process to protect data privacy.

[0084] The server analyzes all the collected data and generates digital profiles of the residents. This analysis uses a generative AI model to obtain profiles that reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars that mimic the residents' thoughts and behaviors.

[0085] This avatar is used to perform simulations within a virtual environment called a digital twin. A digital twin is a virtual space that precisely replicates a real city and is used to evaluate urban planning proposals. Through this simulation, the server analyzes the social impact and effectiveness of the proposed plan.

[0086] Furthermore, the server provides local currency as a reward to residents. This is calculated based on the amount of data residents provide and is credited to the user's account. The terminal displays a notification of receipt of the local currency, informing residents of the result and providing an incentive for further data provision.

[0087] For example, when establishing a new sports facility in a city, the server can analyze residents' movement data and survey results to simulate the facility's placement on a digital twin. Based on these results, it can help to evaluate the impact the sports facility will have on the local community and develop a more appropriate plan.

[0088] An example of a prompt message for a generated AI model is: "Based on residents' opinions and behavioral data, simulate the impact of a new commercial facility and suggest its location."

[0089] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0090] Step 1:

[0091] The terminal presents the user with a questionnaire received from the server. Input is the questionnaire data sent from the server, and output is the questionnaire screen displayed to the user. The terminal utilizes a graphical user interface to create an environment where the user can comfortably input their answers. The user inputs their answers to the presented questions.

[0092] Step 2:

[0093] Once the user has finished entering their answers to the survey, the device sends that data to the server. The input is the user's response data, and the output is encrypted response data sent to the server. The device uses a secure protocol to transmit the data in order to maintain its confidentiality.

[0094] Step 3:

[0095] The server receives the collected response data and stores it in a database. The input is encrypted response data received from the terminal, and the output is the organized and stored response database. The server utilizes a database management system to prepare this data for analysis and performs data cleansing as needed.

[0096] Step 4:

[0097] The server receives daily behavioral data of residents collected by IoT sensors. The input is behavioral data sent from the sensors, and the output is a behavioral dataset organized for analysis. The server uses data mining techniques to extract patterns based on time and location information.

[0098] Step 5:

[0099] The server collects data through social media APIs with the permission of the users. The input is publicly available social media data, and the output is a usable feedback dataset. The server filters posts and activity history through API calls, obtaining the necessary information while respecting privacy.

[0100] Step 6:

[0101] The server integrates these different datasets to generate digital profiles of residents. The input is integrated information from response data, behavioral data, and social media data, and the output is the digital profile of each resident. A generative AI model is used to analyze this data and create profiles that reflect the residents' thought patterns and behavioral characteristics.

[0102] Step 7:

[0103] The server generates avatars based on digital profiles. The input is the resident's digital profile, and the output is an avatar usable in the virtual environment. This avatar is designed to simulate the resident's characteristics.

[0104] Step 8:

[0105] The server runs a simulation using avatars on a digital twin. The input is the initial settings for the avatars and digital twin, and the output is the simulation result data. The simulation is conducted based on a specific urban planning proposal, and data is collected to evaluate its impact.

[0106] Step 9:

[0107] The server analyzes the simulation results and generates urban planning information. The input is the result data obtained from the simulation, and the output is optimized design information for the proposed plan. The server uses this information to adjust parameters and create new proposals.

[0108] Step 10:

[0109] The server awards local currency to residents as compensation for providing data. The input is the amount of data and the value of the transactions provided by the residents, and the output is information about the awarded local currency. The terminal displays notifications to the user regarding the acquired currency, encouraging them to provide further data.

[0110] (Application Example 1)

[0111] 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."

[0112] Improving work efficiency and safety within factories is essential for economically sustainable operations. However, conventional methods do not adequately optimize worker movement, resulting in unnecessary travel and decreased productivity. Furthermore, there is a lack of appropriate incentives for data providers, making them less motivated to cooperate.

[0113] 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.

[0114] In this invention, the server includes means for managing survey data collected from residents, means for connecting residents' behavioral data to sensors, and means for collecting social media data to which residents have consented. This makes it possible to collect movement data of factory workers and propose optimized movement routes based on their digital profiles. Furthermore, it enhances motivation for cooperation by appropriately awarding virtual currency as a reward based on the provided data.

[0115] "Survey data" refers to data on opinions and desires collected from individuals or groups, and is used to gather information for a specific purpose.

[0116] "Behavioral data" refers to data collected using sensors and other means to understand a person's movements and activities, and is used to understand that person's behavioral patterns.

[0117] A "sensor" is a device that detects physical or environmental changes in order to acquire specific information, and is used for data collection.

[0118] "Social media data" refers to data related to information and statements that individuals post on online platforms, and serves as material for understanding individuals' interests and thoughts.

[0119] A "digital profile" refers to a digital representation of an individual's characteristics and behaviors, generated by analyzing collected data, and serves as the basis for mimicking an individual's features.

[0120] An "avatar" is a data model that simulates the thoughts and actions of an individual in the real world, generated based on a digital profile.

[0121] "Digital space" refers to a computer environment that virtually reproduces the real world and is used for virtualization processing and simulations.

[0122] "Virtualization processing" is a process that involves operating avatars in a digital space to simulate specific scenarios, and is used for solving problems in the real world.

[0123] "Environmental design" refers to design work planned to improve the efficiency and usability of physical or digital spaces.

[0124] "Motion data" refers to data that shows how individuals or devices are operating, and is used to optimize movement patterns.

[0125] "Cryptocurrency" is a type of currency traded digitally, which functions as an incentive and is offered as a reward.

[0126] A "user interface" refers to the point of contact between a system and a human being, designed to make it easy for the user to input information and view results.

[0127] "Notification" refers to the act or means of informing the parties of the outcome according to predetermined conditions.

[0128] The system that realizes this application integrates numerous devices and technologies to improve operational efficiency within the factory. The program operates through the steps of data collection, analysis, simulation in a virtual space, optimization suggestions, and incentive provision.

[0129] The server first collects real-time motion data of workers and equipment using sensor devices placed throughout the factory. This data is recorded based on location and time. XYZ sensors are used as the sensor devices, and communication is conducted using the MQTT protocol.

[0130] Next, the server uses Python data analysis libraries (e.g., Pandas, NumPy) to analyze the collected data in detail and generate digital profiles. This clarifies the behavioral patterns of individual workers and equipment. These profiles are used to generate avatars, which operate in a digital space built using Unity.

[0131] In the digital space, a server performs virtualization processing and simulates the avatar's movements. Through this simulation, it is possible to propose the optimal work route based on motion data. This result is provided to the worker via a user interface.

[0132] Users can receive suggestions on their smartphones and other devices to improve their work efficiency. In return for cooperating by providing data, the server will reward them with cryptocurrency and notify them of the reward results.

[0133] As a concrete example, in a food manufacturing plant, there are numerous work processes. By having the system suggest the optimal route for workers to move efficiently along the production line, unnecessary movements can be reduced and production efficiency can be increased.

[0134] Examples of prompts for a generative AI model are as follows:

[0135] "To optimize workflow within the factory, please analyze current worker movement data and calculate the optimal route."

[0136] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0137] Step 1:

[0138] The server collects motion data from sensor devices placed throughout the factory. As input, location and time data for each worker and piece of equipment are acquired in real time from the sensor devices (e.g., XYZ sensors). As output, this data is aggregated on the server and stored in a temporary database. The MQTT protocol is used for communication between the sensor devices and the server.

[0139] Step 2:

[0140] The server analyzes the collected motion data using Python data analysis libraries (Pandas, NumPy). The input is the motion data collected in step 1. The server processes the data and extracts the behavioral patterns of workers and equipment. The output is a digital profile containing the behavioral patterns of each individual. This profile is used in subsequent simulation processing.

[0141] Step 3:

[0142] The server generates an avatar in a digital space built using Unity, based on the generated digital profile. The digital profile obtained in step 2 is used as input. The output is the avatar being placed in the virtual environment and becoming executable. Specifically, the server incorporates the profile data into a Unity script and sets up actions corresponding to the avatar.

[0143] Step 4:

[0144] The server simulates the avatar's movements within the virtual space. As input, the avatar prepared in step 3 operates within the virtual space. Based on the movement data, the server analyzes the worker's movements by simulating multiple scenarios. As output, optimal movement paths and improvement suggestions are generated. These results are provided to the user in the next step.

[0145] Step 5:

[0146] The server notifies the user of the optimized workflow suggestion. The optimized workflow obtained in step 4 is used as input. As output, a notification is sent to a device such as a smartphone, allowing the worker to check the workflow in real time and follow the instructions. Specifically, the information is displayed on the user interface through the notification system.

[0147] Step 6:

[0148] The server distributes cryptocurrency as a reward for providing data. The input is the quantity and quality of the exercise data initially collected, which serve as evaluation criteria. The output is the distribution of rewards, with the cryptocurrency added to the user's account. Specifically, the server applies a reward calculation algorithm and notifies the user of the results through a notification system.

[0149] 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.

[0150] This invention is a system that incorporates an emotion engine into the system to analyze residents' emotional data in real time and continuously, and reflect this data in urban planning. This makes it possible to formulate more appropriate urban plans that take residents' emotions into consideration.

[0151] First, the device displays a questionnaire to residents, and users respond, sending their answers in a format that also includes emotional data. The device then transfers this questionnaire data to a server.

[0152] Next, IoT sensors and emotion engines installed in the devices detect and analyze residents' daily behavioral data and the physiological changes that occur during those activities. For example, this involves using cameras to read facial expressions and analyzing changes in voice tone from audio. This data is also collected on a server and incorporated as part of the residents' digital profiles.

[0153] The server receives the data analysis results from the emotion engine and integrates them with residents' behavioral data and survey results. This generates a digital profile that more precisely reflects the residents' thought patterns and emotional characteristics. Based on the generated profile, the server creates an avatar that takes the residents' emotions into account.

[0154] This avatar is used in a simulation within a digital twin to evaluate how emotional changes affect urban planning. The server analyzes the simulation results and generates information useful for developing urban plans that take emotional data into account.

[0155] Furthermore, the server awards local currency based on the data provided by residents. The provision of emotional data is also included in the evaluation, and appropriate incentives are provided. The terminal notifies residents of this, encouraging their active participation in future data provision.

[0156] For example, when considering the introduction of a new transportation system in a community, the server uses data, including changes in residents' emotions, to perform simulations. By evaluating the predicted increases in stress and satisfaction through emotional data, it becomes possible to analyze the social impact of the introduction in more detail and consider the optimal implementation method.

[0157] Thus, the present invention provides a system that supports highly accurate urban planning that takes emotional data into consideration, and can contribute to improving resident satisfaction.

[0158] The following describes the processing flow.

[0159] Step 1:

[0160] The terminal displays a questionnaire to residents. Users answer the questionnaire and input data, including questions related to emotions. The terminal sends the response data to the server.

[0161] Step 2:

[0162] IoT sensors and an emotion engine built into the device collect behavioral and physiological data from residents' daily activities. For example, cameras and microphones are used to analyze residents' emotions from their facial expressions and voices. The device then transfers this data to a server.

[0163] Step 3:

[0164] The server integrates survey data, sentiment data, and behavioral data to generate digital profiles for each resident. Here, the analysis data from the sentiment engine plays a crucial role.

[0165] Step 4:

[0166] The server creates an avatar that reflects the thoughts and feelings of the resident based on the generated digital profile. This avatar is designed to reflect the user's personality while also mimicking their emotional responses.

[0167] Step 5:

[0168] The server runs simulations on a digital twin. Through avatars, it tests different urban planning scenarios, including the impact of emotions. The server analyzes the changes in residents' emotions in each scenario.

[0169] Step 6:

[0170] The server generates urban planning information, including emotional data, based on simulation results, and then evaluates and optimizes it. This information is used to formulate plans that take into account the emotional needs of residents.

[0171] Step 7:

[0172] The server awards local currency based on data and sentiment information provided by residents. The terminal sends a notification to the user regarding the currency award and prompts them to provide data again.

[0173] Through this processing flow, it is possible to effectively utilize emotional data and formulate high-quality urban plans.

[0174] (Example 2)

[0175] 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".

[0176] In modern urban planning, the feelings and opinions of residents are often not adequately considered, leading to resident dissatisfaction and inappropriate urban environments. This problem stems from the fact that traditional survey methods make it difficult to grasp the deep-seated feelings and characteristics of residents, thus hindering qualitative improvements in urban planning. Furthermore, the lack of effective incentives to gain resident cooperation is another challenge.

[0177] 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.

[0178] In this invention, the server includes means for managing information data collected from residents, means for connecting to an observation device for collecting residents' behavioral data, and means for collecting information source data to which residents have consented. This enables highly accurate urban planning that takes residents' emotions into account by generating and applying digital features based on residents' emotional data. Furthermore, providing local resources as an incentive can encourage active participation from residents.

[0179] "Information data" refers to all data collected from residents, including opinions and feelings, and includes information from surveys and social media.

[0180] "Observation equipment" refers to devices used to detect residents' movements and physiological changes, including cameras and microphones. The data collected is then used for emotional analysis of residents.

[0181] "Source data" refers to data collected with the consent of residents and includes data from social media and other public information infrastructure.

[0182] "Digital features" are virtual profiles that represent the emotions and behavioral characteristics of residents, generated based on collected information data and data obtained from observation devices.

[0183] A "virtual entity" is an avatar generated based on digital characteristics, referring to a digital being that mimics the emotions and behavioral patterns of residents.

[0184] A "digital environment" refers to a simulation space where simulated experiments are conducted based on virtual entities, and is used to evaluate the impact of urban planning in advance.

[0185] A "simulated experiment" refers to the process of evaluating the impact of urban planning scenarios on residents by operating virtual entities within a digital environment.

[0186] "Urban planning" refers to a plan for the ideal form of a city and the placement of facilities that better meets the needs of residents, based on emotional data and the results of simulated experiments.

[0187] "Local resources" refer to resources that have value as rewards based on data provided by residents, and include local currencies and points.

[0188] The objective of this invention is to provide a system that supports highly accurate urban planning based on residents' emotional data. The system primarily operates through the cooperation of a server, terminals, and users, systematically collecting and analyzing residents' emotional data.

[0189] The server manages residents' informational and behavioral data, and generates digital characteristics based on this data. The analysis engine within the server makes full use of various data collection methods to form digital characteristics that reflect the thought patterns and emotional traits of each individual resident. This involves observation devices to monitor residents' daily behavior and data sources obtained with the residents' consent.

[0190] The terminal displays a survey for residents and sends the results to a server. The survey includes questions designed to reflect residents' emotions, allowing for detailed collection of their opinions. In addition, the terminal has a built-in camera and microphone, which sense changes in facial expressions and voice, and transmit this emotion data to the server.

[0191] Users provide their emotional state through their devices by answering questionnaires. The data collected through user participation is used for analysis on the server and evaluated as a candidate for regional resource allocation.

[0192] Specifically, when developing urban planning for the construction of new public facilities based on residents' sentiment data, the server first generates digital characteristics by integrating survey data and behavioral data from residents, and then derives optimal placement and design proposals based on the results.

[0193] An example of a prompt is, "Please tell me how to formulate an urban plan that takes into account residents' sentiment data when constructing a new public facility in a certain area." By inputting this prompt into the generating AI model, it will be supported in generating urban planning proposals that are more in line with the needs of residents.

[0194] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0195] Step 1:

[0196] The terminal displays a questionnaire to residents. The questionnaire includes questions that ask about residents' current feelings and opinions. When users answer the questionnaire, input data is generated. The terminal collects this input data and sends it to the server. The server classifies the received questionnaire data according to its content and stores it in a database.

[0197] Step 2:

[0198] The device uses its built-in camera and microphone to detect changes in residents' facial expressions and voices. As users perform their daily activities, these sensors acquire facial expression and voice data. Based on the acquired data, the emotion engine analyzes the data using image and voice analysis algorithms. The analysis results are output as emotion parameters and sent to the server.

[0199] Step 3:

[0200] The server integrates survey data and sentiment data received from terminals. Using data mining techniques, the server models residents' thought patterns and emotional characteristics. During this process, various data are processed using feature extraction and output as integrated digital features. The server stores these generated digital features in a database.

[0201] Step 4:

[0202] The server generates avatars that mimic the emotions of the residents based on the generated digital features. A generative AI model is used, and the avatar's parameters are set based on the input digital features. The output avatars are saved in preparation for simulation in a digital twin environment.

[0203] Step 5:

[0204] The server conducts simulated experiments using generated avatars in a digital twin environment. The simulation evaluates the impact of various urban planning scenarios on the avatars. The output of this simulation serves as a guideline for improving urban planning, taking emotional data into consideration.

[0205] Step 6:

[0206] The server analyzes the simulation results and extracts information on urban planning. The information obtained from the analysis is used to support local government decision-making. The server documents this information and provides it to the relevant departments through an interface.

[0207] Step 7:

[0208] The server provides residents with local resources as an incentive for providing data. The incentive is calculated based on the amount and value of the data provided by the resident. The terminal receives the calculation result and notifies the user, encouraging participation in future data provision.

[0209] (Application Example 2)

[0210] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0211] In modern urban environments, there is a growing need to utilize residents' emotional data to optimize urban design and commercial spaces. However, conventional methods of collecting emotional data are fragmented and fail to fundamentally improve residents' satisfaction. To solve this problem, a system is needed that can analyze residents' emotions in real time and quickly reflect appropriate measures based on that analysis.

[0212] 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.

[0213] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detector for collecting residents' activity data, and means for analyzing customers' physiological changes with an image capture device and extracting emotional data. This enables high-precision collection and analysis of residents' emotional data, allowing for rapid feedback for urban design and optimization of commercial spaces.

[0214] "Opinion data" refers to information that reflects an individual's thoughts and perceptions, based on surveys and feedback collected from residents.

[0215] "Activity data" refers to information about residents' daily actions and travel routes, which is collected by detectors.

[0216] "Online platform data" refers to information about social media and web activities that are provided with the consent of residents.

[0217] "Digital characteristics" refer to data that indicates the characteristics and tendencies of residents, generated by analyzing their opinion data and activity data.

[0218] A "virtual space" is a virtual environment based on the digital characteristics of residents simulated on a computer.

[0219] A "simulated experiment" is a simulation that observes the movements and reactions of avatars in a virtual space based on the digital characteristics of the residents, and analyzes the results.

[0220] An "image capture device" is a device, such as a camera or sensor, that captures and analyzes the facial expressions and movements of residents and customers.

[0221] "Emotional data" refers to data that indicates the emotional state extracted by analyzing the physiological changes of residents based on information obtained from image capture devices.

[0222] "Rewards" refer to local currency or other incentives given to residents for the information they provide.

[0223] The system used to realize this application involves collecting residents' emotional data with high accuracy and providing rapid feedback for urban design and the optimization of commercial spaces.

[0224] The server manages opinion data obtained from residents and collects activity data and physiological changes using IoT sensors and image capture devices. Terminals connected to the server, for example, capture customers' facial expressions in real time using cameras mounted on smart glasses and collect data to generate digital characteristics. OpenCV is used as the image processing software, and AWS® or Google® Cloud is used as the cloud solution.

[0225] Emotional data collected by the terminal is analyzed by a generative AI model in the cloud and sent to a server. The server uses this data to prepare real-time responses to residents and customers. An example of a prompt message would be, "Start facial analysis the moment the customer picks up the product, send the data to the server, and display the most appropriate customer service response on the glasses in real time." In this way, the present invention can provide a highly accurate urban planning support system that takes residents' emotional data into account, thereby contributing to improved resident satisfaction.

[0226] For example, imagine a scenario in a commercial facility where a store employee wearing smart glasses interacts with a customer, and the customer's emotional state is fed back to the employee in real time via the glasses' display. This allows the employee to tailor their service to each individual customer's emotions, thereby improving the customer experience.

[0227] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0228] Step 1:

[0229] The smart glasses within the device capture the customer's face and acquire image data in real time. The input is video from the camera built into the glasses, and the output is image data as a still image or video. This data is used as initial input for image processing.

[0230] Step 2:

[0231] The device analyzes the acquired image data using OpenCV to extract feature points from the customer's face. This process generates digital information representing subtle facial movements and expressions. The input is the image data obtained in step 1, and the output is numerical data including facial feature points.

[0232] Step 3:

[0233] The device uses feature points obtained through image processing to determine the emotional state. It utilizes a generative AI model to map feature points to emotional labels. The input is facial feature data, and the output is a label indicating the emotional state (e.g., joy, anger, surprise, etc.).

[0234] Step 4:

[0235] The determined emotional state is sent to a server connected to the cloud. The server receives this data, analyzes it, and uses it to generate information relevant to commercial activities. The input is the emotional state label, and the output is the initial dataset used for analysis.

[0236] Step 5:

[0237] The server uses a generative AI model to analyze emotional state data. It generates appropriate customer service methods and business strategies, taking into account real-time responses to customers. The input is the dataset obtained in step 4, and the output is optimized customer service instructions and strategies.

[0238] Step 6:

[0239] The generated customer service instructions and strategies are displayed on the smart glasses. The staff receive the instructions on the display and use them to interact with customers. The input is customer service instructions from the server, and the output is visual information for the staff.

[0240] Step 7:

[0241] Users respond to customers based on information displayed on their glasses and incorporate the results into their daily work. User feedback is also used to improve the next data collection and analysis process. The input is the information displayed on the glasses' screen, and the output is customer satisfaction and commercial results.

[0242] 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.

[0243] 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.

[0244] 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.

[0245] [Second Embodiment]

[0246] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0247] 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.

[0248] 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).

[0249] 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.

[0250] 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.

[0251] 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).

[0252] 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.

[0253] 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.

[0254] 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.

[0255] 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.

[0256] 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.

[0257] 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".

[0258] This invention is a system for formulating highly accurate urban plans using resident data, and includes the following functions.

[0259] First, a questionnaire is presented to residents via a device. Users answer the questions presented through the device, and these answers are sent from the device to the server. At this stage, data regarding residents' personal opinions and wishes is collected.

[0260] Next, IoT sensors are used to automatically acquire data on residents' daily activities. The acquired activity data is transferred to a server via a terminal. During this process, location information and residents' movements at specific times are recorded.

[0261] Furthermore, the server collects social media data to the extent permitted by the residents. This is done via the APIs of social media platforms, making it possible to obtain residents' public statements and activity history.

[0262] This data is integrated and analyzed on a server to generate digital profiles of residents. These digital profiles reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars. These avatars mimic the residents' thoughts and behaviors and are used in simulations on the digital twin.

[0263] A digital twin is a virtual environment that recreates a real city in a virtual space, and is used to run simulations using avatars. The server evaluates the effectiveness of urban planning proposals through simulations, analyzes the obtained data, and derives the optimal urban design.

[0264] In this process, residents are offered local currency as a reward for cooperating by providing data. The server calculates the local currency based on the data provided and adds it to the user's account. The terminal displays a notification to the user that they have received the local currency, playing a role in encouraging residents to provide further data.

[0265] For example, when considering the establishment of a new park in a city, the server analyzes resident movement data and survey results, and runs a simulation of the park's placement on a digital twin. Based on these results, it becomes possible to concretely understand the social value and impact that the park would bring and to formulate an appropriate plan.

[0266] Thus, the present invention provides a system that makes it possible to improve the accuracy of urban planning through resident-participatory data collection and analysis.

[0267] The following describes the processing flow.

[0268] Step 1:

[0269] The terminal presents a questionnaire to the resident. The user answers the questions on the terminal and presses the submit button upon completion. The terminal then sends the collected response data to the server.

[0270] Step 2:

[0271] IoT sensors automatically detect residents' location and activity information. The device receives this data from the sensor and transfers it to the server.

[0272] Step 3:

[0273] The server collects relevant information through social media APIs that residents have previously authorized. The server stores the collected data in an internal database.

[0274] Step 4:

[0275] The server integrates and analyzes survey data, behavioral data, and social media data. Using this data, the server generates digital profiles of residents.

[0276] Step 5:

[0277] Based on the generated digital profile, the server uses a generator AI to create an avatar that possesses the residents' thought patterns and behavioral characteristics.

[0278] Step 6:

[0279] The server runs simulations using avatars on a digital twin. Through these simulations, the server evaluates the effectiveness of proposed urban planning solutions.

[0280] Step 7:

[0281] The server analyzes the simulation results and generates the information necessary for urban planning. The generated information is compiled as materials useful for improving urban planning.

[0282] Step 8:

[0283] The server calculates the amount of local currency to be assigned to each user based on the data provided.

[0284] Step 9:

[0285] The server assigns the calculated local currency to the user's account. The terminal displays a notification to the user about the received local currency.

[0286] (Example 1)

[0287] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] In modern urban development, it is required to reflect the diverse opinions of residents and formulate a precise regional plan. However, with conventional methods, it is difficult to fully model the activities and thoughts of residents, and it is difficult to formulate an urban plan that conforms to the actual lifestyle. In addition, the provision of incentives to residents is insufficient, and there is also a lack of a mechanism to elicit cooperation in data provision.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following respective means.

[0290] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detection device for collecting the behavior data of residents, and means for collecting public data consented to by residents. Thereby, it becomes possible to formulate a precise regional plan that reflects the thinking patterns of residents.

[0291] "Residents" refers to individuals or groups living in a city or region, and are the providers of survey responses and behavioral data.

[0292] "Opinion data" refers to information about the thoughts and wishes expressed by residents through surveys and feedback.

[0293] "Behavioral data" refers to information about residents' daily movements and activities, and is acquired by detection devices.

[0294] A "detection device" refers to hardware used to sense residents' behavior and the environment and collect data.

[0295] "Public data" refers to information about statements and activity history that residents have made public on social media, etc.

[0296] "Digital information" refers to digitized profiles of residents generated by analyzing their opinion data, behavioral data, and publicly available data.

[0297] "Virtual representation" refers to digital characters and models generated based on the digital information of residents.

[0298] A "virtual environment" refers to a 3D or simulated space created on a computer, and is used in urban planning simulations.

[0299] "Simulation" is a process of conducting experiments using virtual representations within a virtual environment to evaluate the effectiveness of urban planning.

[0300] "Rewards" refer to local currency or perks given as incentives to residents for the data they provide.

[0301] A "local currency" is a unique currency that can be used within a specific region and is given to residents as a reward.

[0302] The present invention is a system for formulating an advanced urban development plan with the participation of residents. Embodiments of the system will be described below.

[0303] This system first presents a questionnaire to residents via a terminal. The terminal has a graphical user interface (GUI) and provides a screen that can be easily operated by residents. The user can answer the presented questions using this terminal. These response data are securely transmitted to the server using encryption technology.

[0304] Next, the system utilizes IoT sensors to collect daily behavior data of residents. This consists of a GPS module for acquiring location information and a motion sensor for detecting specific activities, etc. The collected data is transmitted to the server via the terminal. The server integrates these data in a cloud environment and manages them centrally.

[0305] Furthermore, the server collects public statements and activity histories of residents through the API of social media only when the residents consent. In this process, access management for protecting data privacy is performed.

[0306] The server analyzes all the collected data and generates a digital profile of the residents. For this analysis, a generative AI model is used to obtain a profile that reflects the thinking patterns and behavior characteristics of the residents. Based on this profile, the server generates an avatar that mimics the thinking and behavior of the residents.

[0307] This avatar is used to perform simulations within a virtual environment called a digital twin. The digital twin is a virtual space that precisely reproduces the real city and is useful for evaluating urban planning proposals. The server analyzes the social impact and effectiveness of the planning proposal through this simulation.

[0308] Furthermore, the server provides local currency as a reward to residents. This is calculated based on the amount of data residents provide and is credited to the user's account. The terminal displays a notification of receipt of the local currency, informing residents of the result and providing an incentive for further data provision.

[0309] For example, when establishing a new sports facility in a city, the server can analyze residents' movement data and survey results to simulate the facility's placement on a digital twin. Based on these results, it can help to evaluate the impact the sports facility will have on the local community and develop a more appropriate plan.

[0310] An example of a prompt message for a generated AI model is: "Based on residents' opinions and behavioral data, simulate the impact of a new commercial facility and suggest its location."

[0311] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0312] Step 1:

[0313] The terminal presents the user with a questionnaire received from the server. Input is the questionnaire data sent from the server, and output is the questionnaire screen displayed to the user. The terminal utilizes a graphical user interface to create an environment where the user can comfortably input their answers. The user inputs their answers to the presented questions.

[0314] Step 2:

[0315] Once the user has finished entering their answers to the survey, the device sends that data to the server. The input is the user's response data, and the output is encrypted response data sent to the server. The device uses a secure protocol to transmit the data in order to maintain its confidentiality.

[0316] Step 3:

[0317] The server receives the collected response data and stores it in a database. The input is encrypted response data received from the terminal, and the output is the organized and stored response database. The server utilizes a database management system to prepare this data for analysis and performs data cleansing as needed.

[0318] Step 4:

[0319] The server receives daily behavioral data of residents collected by IoT sensors. The input is behavioral data sent from the sensors, and the output is a behavioral dataset organized for analysis. The server uses data mining techniques to extract patterns based on time and location information.

[0320] Step 5:

[0321] The server collects data through social media APIs with the permission of the users. The input is publicly available social media data, and the output is a usable feedback dataset. The server filters posts and activity history through API calls, obtaining the necessary information while respecting privacy.

[0322] Step 6:

[0323] The server integrates these different datasets to generate digital profiles of residents. The input is integrated information from response data, behavioral data, and social media data, and the output is the digital profile of each resident. A generative AI model is used to analyze this data and create profiles that reflect the residents' thought patterns and behavioral characteristics.

[0324] Step 7:

[0325] The server generates avatars based on digital profiles. The input is the resident's digital profile, and the output is an avatar usable in the virtual environment. This avatar is designed to simulate the resident's characteristics.

[0326] Step 8:

[0327] The server runs a simulation using avatars on a digital twin. The input is the initial settings for the avatars and digital twin, and the output is the simulation result data. The simulation is conducted based on a specific urban planning proposal, and data is collected to evaluate its impact.

[0328] Step 9:

[0329] The server analyzes the simulation results and generates urban planning information. The input is the result data obtained from the simulation, and the output is optimized design information for the proposed plan. The server uses this information to adjust parameters and create new proposals.

[0330] Step 10:

[0331] The server awards local currency to residents as compensation for providing data. The input is the amount of data and the value of the transactions provided by the residents, and the output is information about the awarded local currency. The terminal displays notifications to the user regarding the acquired currency, encouraging them to provide further data.

[0332] (Application Example 1)

[0333] 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."

[0334] Improving work efficiency and safety within factories is essential for economically sustainable operations. However, conventional methods do not adequately optimize worker movement, resulting in unnecessary travel and decreased productivity. Furthermore, there is a lack of appropriate incentives for data providers, making them less motivated to cooperate.

[0335] 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.

[0336] In this invention, the server includes means for managing survey data collected from residents, means for connecting residents' behavioral data to sensors, and means for collecting social media data to which residents have consented. This makes it possible to collect movement data of factory workers and propose optimized movement routes based on their digital profiles. Furthermore, it enhances motivation for cooperation by appropriately awarding virtual currency as a reward based on the provided data.

[0337] "Survey data" refers to data on opinions and desires collected from individuals or groups, and is used to gather information for a specific purpose.

[0338] "Behavioral data" refers to data collected using sensors and other means to understand a person's movements and activities, and is used to understand that person's behavioral patterns.

[0339] A "sensor" is a device that detects physical or environmental changes in order to acquire specific information, and is used for data collection.

[0340] "Social media data" refers to data related to information and statements that individuals post on online platforms, and serves as material for understanding individuals' interests and thoughts.

[0341] A "digital profile" refers to a digital representation of an individual's characteristics and behaviors, generated by analyzing collected data, and serves as the basis for mimicking an individual's features.

[0342] An "avatar" is a data model that simulates the thoughts and actions of an individual in the real world, generated based on a digital profile.

[0343] "Digital space" refers to a computer environment that virtually reproduces the real world and is used for virtualization processing and simulations.

[0344] "Virtualization processing" is a process that involves operating avatars in a digital space to simulate specific scenarios, and is used for solving problems in the real world.

[0345] "Environmental design" refers to design work planned to improve the efficiency and usability of physical or digital spaces.

[0346] "Motion data" refers to data that shows how individuals or devices are operating, and is used to optimize movement patterns.

[0347] "Cryptocurrency" is a type of currency traded digitally, which functions as an incentive and is offered as a reward.

[0348] A "user interface" refers to the point of contact between a system and a human being, designed to make it easy for the user to input information and view results.

[0349] "Notification" refers to the act or means of informing the parties of the outcome according to predetermined conditions.

[0350] The system that realizes this application integrates numerous devices and technologies to improve operational efficiency within the factory. The program operates through the steps of data collection, analysis, simulation in a virtual space, optimization suggestions, and incentive provision.

[0351] The server first collects real-time motion data of workers and equipment using sensor devices placed throughout the factory. This data is recorded based on location and time. XYZ sensors are used as the sensor devices, and communication is conducted using the MQTT protocol.

[0352] Next, the server uses Python data analysis libraries (e.g., Pandas, NumPy) to analyze the collected data in detail and generate digital profiles. This clarifies the behavioral patterns of individual workers and equipment. These profiles are used to generate avatars, which operate in a digital space built using Unity.

[0353] In the digital space, a server performs virtualization processing and simulates the avatar's movements. Through this simulation, it is possible to propose the optimal work route based on motion data. This result is provided to the worker via a user interface.

[0354] Users can receive suggestions on their smartphones and other devices to improve their work efficiency. In return for cooperating by providing data, the server will reward them with cryptocurrency and notify them of the reward results.

[0355] As a concrete example, in a food manufacturing plant, there are numerous work processes. By having the system suggest the optimal route for workers to move efficiently along the production line, unnecessary movements can be reduced and production efficiency can be increased.

[0356] Examples of prompts for a generative AI model are as follows:

[0357] "To optimize workflow within the factory, please analyze current worker movement data and calculate the optimal route."

[0358] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0359] Step 1:

[0360] The server collects motion data from sensor devices placed throughout the factory. As input, location and time data for each worker and piece of equipment are acquired in real time from the sensor devices (e.g., XYZ sensors). As output, this data is aggregated on the server and stored in a temporary database. The MQTT protocol is used for communication between the sensor devices and the server.

[0361] Step 2:

[0362] The server analyzes the collected motion data using Python data analysis libraries (Pandas, NumPy). The input is the motion data collected in step 1. The server processes the data and extracts the behavioral patterns of workers and equipment. The output is a digital profile containing the behavioral patterns of each individual. This profile is used in subsequent simulation processing.

[0363] Step 3:

[0364] The server generates an avatar in a digital space built using Unity, based on the generated digital profile. The digital profile obtained in step 2 is used as input. The output is the avatar being placed in the virtual environment and becoming executable. Specifically, the server incorporates the profile data into a Unity script and sets up actions corresponding to the avatar.

[0365] Step 4:

[0366] The server simulates the avatar's movements within the virtual space. As input, the avatar prepared in step 3 operates within the virtual space. Based on the movement data, the server analyzes the worker's movements by simulating multiple scenarios. As output, optimal movement paths and improvement suggestions are generated. These results are provided to the user in the next step.

[0367] Step 5:

[0368] The server notifies the user of the optimized workflow suggestion. The optimized workflow obtained in step 4 is used as input. As output, a notification is sent to a device such as a smartphone, allowing the worker to check the workflow in real time and follow the instructions. Specifically, the information is displayed on the user interface through the notification system.

[0369] Step 6:

[0370] The server distributes cryptocurrency as a reward for providing data. The input is the quantity and quality of the exercise data initially collected, which serve as evaluation criteria. The output is the distribution of rewards, with the cryptocurrency added to the user's account. Specifically, the server applies a reward calculation algorithm and notifies the user of the results through a notification system.

[0371] 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.

[0372] This invention is a system that incorporates an emotion engine into the system to analyze residents' emotional data in real time and continuously, and reflect this data in urban planning. This makes it possible to formulate more appropriate urban plans that take residents' emotions into consideration.

[0373] First, the device displays a questionnaire to residents, and users respond, sending their answers in a format that also includes emotional data. The device then transfers this questionnaire data to a server.

[0374] Next, IoT sensors and emotion engines installed in the devices detect and analyze residents' daily behavioral data and the physiological changes that occur during those activities. For example, this involves using cameras to read facial expressions and analyzing changes in voice tone from audio. This data is also collected on a server and incorporated as part of the residents' digital profiles.

[0375] The server receives the data analysis results from the emotion engine and integrates them with residents' behavioral data and survey results. This generates a digital profile that more precisely reflects the residents' thought patterns and emotional characteristics. Based on the generated profile, the server creates an avatar that takes the residents' emotions into account.

[0376] This avatar is used in a simulation within a digital twin to evaluate how emotional changes affect urban planning. The server analyzes the simulation results and generates information useful for developing urban plans that take emotional data into account.

[0377] Furthermore, the server awards local currency based on the data provided by residents. The provision of emotional data is also included in the evaluation, and appropriate incentives are provided. The terminal notifies residents of this, encouraging their active participation in future data provision.

[0378] For example, when considering the introduction of a new transportation system in a community, the server uses data, including changes in residents' emotions, to perform simulations. By evaluating the predicted increases in stress and satisfaction through emotional data, it becomes possible to analyze the social impact of the introduction in more detail and consider the optimal implementation method.

[0379] Thus, the present invention provides a system that supports highly accurate urban planning that takes emotional data into consideration, and can contribute to improving resident satisfaction.

[0380] The following describes the processing flow.

[0381] Step 1:

[0382] The terminal displays a questionnaire to residents. Users answer the questionnaire and input data, including questions related to emotions. The terminal sends the response data to the server.

[0383] Step 2:

[0384] IoT sensors and an emotion engine built into the device collect behavioral and physiological data from residents' daily activities. For example, cameras and microphones are used to analyze residents' emotions from their facial expressions and voices. The device then transfers this data to a server.

[0385] Step 3:

[0386] The server integrates survey data, sentiment data, and behavioral data to generate digital profiles for each resident. Here, the analysis data from the sentiment engine plays a crucial role.

[0387] Step 4:

[0388] The server creates an avatar that reflects the thoughts and feelings of the resident based on the generated digital profile. This avatar is designed to reflect the user's personality while also mimicking their emotional responses.

[0389] Step 5:

[0390] The server runs simulations on a digital twin. Through avatars, it tests different urban planning scenarios, including the impact of emotions. The server analyzes the changes in residents' emotions in each scenario.

[0391] Step 6:

[0392] The server generates urban planning information, including emotional data, based on simulation results, and then evaluates and optimizes it. This information is used to formulate plans that take into account the emotional needs of residents.

[0393] Step 7:

[0394] The server awards local currency based on data and sentiment information provided by residents. The terminal sends a notification to the user regarding the currency award and prompts them to provide data again.

[0395] Through this processing flow, it is possible to effectively utilize emotional data and formulate high-quality urban plans.

[0396] (Example 2)

[0397] 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".

[0398] In modern urban planning, the feelings and opinions of residents are often not adequately considered, leading to resident dissatisfaction and inappropriate urban environments. This problem stems from the fact that traditional survey methods make it difficult to grasp the deep-seated feelings and characteristics of residents, thus hindering qualitative improvements in urban planning. Furthermore, the lack of effective incentives to gain resident cooperation is another challenge.

[0399] 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.

[0400] In this invention, the server includes means for managing information data collected from residents, means for connecting to an observation device for collecting residents' behavioral data, and means for collecting information source data to which residents have consented. This enables highly accurate urban planning that takes residents' emotions into account by generating and applying digital features based on residents' emotional data. Furthermore, providing local resources as an incentive can encourage active participation from residents.

[0401] "Information data" refers to all data collected from residents, including opinions and feelings, and includes information from surveys and social media.

[0402] "Observation equipment" refers to devices used to detect residents' movements and physiological changes, including cameras and microphones. The data collected is then used for emotional analysis of residents.

[0403] "Source data" refers to data collected with the consent of residents and includes data from social media and other public information infrastructure.

[0404] "Digital features" are virtual profiles that represent the emotions and behavioral characteristics of residents, generated based on collected information data and data obtained from observation devices.

[0405] A "virtual entity" is an avatar generated based on digital characteristics, referring to a digital being that mimics the emotions and behavioral patterns of residents.

[0406] A "digital environment" refers to a simulation space where simulated experiments are conducted based on virtual entities, and is used to evaluate the impact of urban planning in advance.

[0407] A "simulated experiment" refers to the process of evaluating the impact of urban planning scenarios on residents by operating virtual entities within a digital environment.

[0408] "Urban planning" refers to a plan for the ideal form of a city and the placement of facilities that better meets the needs of residents, based on emotional data and the results of simulated experiments.

[0409] "Local resources" refer to resources that have value as rewards based on data provided by residents, and include local currencies and points.

[0410] The objective of this invention is to provide a system that supports highly accurate urban planning based on residents' emotional data. The system primarily operates through the cooperation of a server, terminals, and users, systematically collecting and analyzing residents' emotional data.

[0411] The server manages residents' informational and behavioral data, and generates digital characteristics based on this data. The analysis engine within the server makes full use of various data collection methods to form digital characteristics that reflect the thought patterns and emotional traits of each individual resident. This involves observation devices to monitor residents' daily behavior and data sources obtained with the residents' consent.

[0412] The terminal displays a survey for residents and sends the results to a server. The survey includes questions designed to reflect residents' emotions, allowing for detailed collection of their opinions. In addition, the terminal has a built-in camera and microphone, which sense changes in facial expressions and voice, and transmit this emotion data to the server.

[0413] Users provide their emotional state through their devices by answering questionnaires. The data collected through user participation is used for analysis on the server and evaluated as a candidate for regional resource allocation.

[0414] Specifically, when developing urban planning for the construction of new public facilities based on residents' sentiment data, the server first generates digital characteristics by integrating survey data and behavioral data from residents, and then derives optimal placement and design proposals based on the results.

[0415] An example of a prompt is, "Please tell me how to formulate an urban plan that takes into account residents' sentiment data when constructing a new public facility in a certain area." By inputting this prompt into the generating AI model, it will be supported in generating urban planning proposals that are more in line with the needs of residents.

[0416] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0417] Step 1:

[0418] The terminal displays a questionnaire to residents. The questionnaire includes questions that ask about residents' current feelings and opinions. When users answer the questionnaire, input data is generated. The terminal collects this input data and sends it to the server. The server classifies the received questionnaire data according to its content and stores it in a database.

[0419] Step 2:

[0420] The device uses its built-in camera and microphone to detect changes in residents' facial expressions and voices. As users perform their daily activities, these sensors acquire facial expression and voice data. Based on the acquired data, the emotion engine analyzes the data using image and voice analysis algorithms. The analysis results are output as emotion parameters and sent to the server.

[0421] Step 3:

[0422] The server integrates survey data and sentiment data received from terminals. Using data mining techniques, the server models residents' thought patterns and emotional characteristics. During this process, various data are processed using feature extraction and output as integrated digital features. The server stores these generated digital features in a database.

[0423] Step 4:

[0424] The server generates avatars that mimic the emotions of the residents based on the generated digital features. A generative AI model is used, and the avatar's parameters are set based on the input digital features. The output avatars are saved in preparation for simulation in a digital twin environment.

[0425] Step 5:

[0426] The server conducts simulated experiments using generated avatars in a digital twin environment. The simulation evaluates the impact of various urban planning scenarios on the avatars. The output of this simulation serves as a guideline for improving urban planning, taking emotional data into consideration.

[0427] Step 6:

[0428] The server analyzes the simulation results and extracts information on urban planning. The information obtained from the analysis is used to support local government decision-making. The server documents this information and provides it to the relevant departments through an interface.

[0429] Step 7:

[0430] The server provides residents with local resources as an incentive for providing data. The incentive is calculated based on the amount and value of the data provided by the resident. The terminal receives the calculation result and notifies the user, encouraging participation in future data provision.

[0431] (Application Example 2)

[0432] 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."

[0433] In modern urban environments, there is a growing need to utilize residents' emotional data to optimize urban design and commercial spaces. However, conventional methods of collecting emotional data are fragmented and fail to fundamentally improve residents' satisfaction. To solve this problem, a system is needed that can analyze residents' emotions in real time and quickly reflect appropriate measures based on that analysis.

[0434] 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.

[0435] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detector for collecting residents' activity data, and means for analyzing customers' physiological changes with an image capture device and extracting emotional data. This enables high-precision collection and analysis of residents' emotional data, allowing for rapid feedback for urban design and optimization of commercial spaces.

[0436] "Opinion data" refers to information that reflects an individual's thoughts and perceptions, based on surveys and feedback collected from residents.

[0437] "Activity data" refers to information about residents' daily actions and travel routes, which is collected by detectors.

[0438] "Online platform data" refers to information about social media and web activities that are provided with the consent of residents.

[0439] "Digital characteristics" refer to data that indicates the characteristics and tendencies of residents, generated by analyzing their opinion data and activity data.

[0440] A "virtual space" is a virtual environment based on the digital characteristics of residents simulated on a computer.

[0441] A "simulated experiment" is a simulation that observes the movements and reactions of avatars in a virtual space based on the digital characteristics of the residents, and analyzes the results.

[0442] An "image capture device" is a device, such as a camera or sensor, that captures and analyzes the facial expressions and movements of residents and customers.

[0443] "Emotional data" refers to data that indicates the emotional state extracted by analyzing the physiological changes of residents based on information obtained from image capture devices.

[0444] "Rewards" refer to local currency or other incentives given to residents for the information they provide.

[0445] The system used to realize this application involves collecting residents' emotional data with high accuracy and providing rapid feedback for urban design and the optimization of commercial spaces.

[0446] The server manages opinion data obtained from residents and collects activity data and physiological changes using IoT sensors and image capture devices. Terminals connected to the server, for example, capture customers' facial expressions in real time using cameras mounted on smart glasses and collect data to generate digital characteristics. OpenCV is used as the image processing software, and AWS or Google Cloud is used as the cloud solution.

[0447] Emotional data collected by the terminal is analyzed by a generative AI model in the cloud and sent to a server. The server uses this data to prepare real-time responses to residents and customers. An example of a prompt message would be, "Start facial analysis the moment the customer picks up the product, send the data to the server, and display the most appropriate customer service response on the glasses in real time." In this way, the present invention can provide a highly accurate urban planning support system that takes residents' emotional data into account, thereby contributing to improved resident satisfaction.

[0448] For example, imagine a scenario in a commercial facility where a store employee wearing smart glasses interacts with a customer, and the customer's emotional state is fed back to the employee in real time via the glasses' display. This allows the employee to tailor their service to each individual customer's emotions, thereby improving the customer experience.

[0449] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0450] Step 1:

[0451] The smart glasses within the device capture the customer's face and acquire image data in real time. The input is video from the camera built into the glasses, and the output is image data as a still image or video. This data is used as initial input for image processing.

[0452] Step 2:

[0453] The device analyzes the acquired image data using OpenCV to extract feature points from the customer's face. This process generates digital information representing subtle facial movements and expressions. The input is the image data obtained in step 1, and the output is numerical data including facial feature points.

[0454] Step 3:

[0455] The device uses feature points obtained through image processing to determine the emotional state. It utilizes a generative AI model to map feature points to emotional labels. The input is facial feature data, and the output is a label indicating the emotional state (e.g., joy, anger, surprise, etc.).

[0456] Step 4:

[0457] The determined emotional state is sent to a server connected to the cloud. The server receives this data, analyzes it, and uses it to generate information relevant to commercial activities. The input is the emotional state label, and the output is the initial dataset used for analysis.

[0458] Step 5:

[0459] The server uses a generative AI model to analyze emotional state data. It generates appropriate customer service methods and business strategies, taking into account real-time responses to customers. The input is the dataset obtained in step 4, and the output is optimized customer service instructions and strategies.

[0460] Step 6:

[0461] The generated customer service instructions and strategies are displayed on the smart glasses. The staff receive the instructions on the display and use them to interact with customers. The input is customer service instructions from the server, and the output is visual information for the staff.

[0462] Step 7:

[0463] Users respond to customers based on information displayed on their glasses and incorporate the results into their daily work. User feedback is also used to improve the next data collection and analysis process. The input is the information displayed on the glasses' screen, and the output is customer satisfaction and commercial results.

[0464] 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.

[0465] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0466] 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.

[0467] [Third Embodiment]

[0468] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0469] 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.

[0470] 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).

[0471] 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.

[0472] 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.

[0473] 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).

[0474] 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.

[0475] 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.

[0476] 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.

[0477] 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.

[0478] 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.

[0479] 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".

[0480] This invention is a system for formulating highly accurate urban plans using resident data, and includes the following functions.

[0481] First, a questionnaire is presented to residents via a device. Users answer the questions presented through the device, and these answers are sent from the device to the server. At this stage, data regarding residents' personal opinions and wishes is collected.

[0482] Next, IoT sensors are used to automatically acquire data on residents' daily activities. The acquired activity data is transferred to a server via a terminal. During this process, location information and residents' movements at specific times are recorded.

[0483] Furthermore, the server collects social media data to the extent permitted by the residents. This is done via the APIs of social media platforms, making it possible to obtain residents' public statements and activity history.

[0484] This data is integrated and analyzed on a server to generate digital profiles of residents. These digital profiles reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars. These avatars mimic the residents' thoughts and behaviors and are used in simulations on the digital twin.

[0485] A digital twin is a virtual environment that recreates a real city in a virtual space, and is used to run simulations using avatars. The server evaluates the effectiveness of urban planning proposals through simulations, analyzes the obtained data, and derives the optimal urban design.

[0486] In this process, residents are offered local currency as a reward for cooperating by providing data. The server calculates the local currency based on the data provided and adds it to the user's account. The terminal displays a notification to the user that they have received the local currency, playing a role in encouraging residents to provide further data.

[0487] For example, when considering the establishment of a new park in a city, the server analyzes resident movement data and survey results, and runs a simulation of the park's placement on a digital twin. Based on these results, it becomes possible to concretely understand the social value and impact that the park would bring and to formulate an appropriate plan.

[0488] Thus, the present invention provides a system that makes it possible to improve the accuracy of urban planning through resident-participatory data collection and analysis.

[0489] The following describes the processing flow.

[0490] Step 1:

[0491] The terminal presents a questionnaire to the resident. The user answers the questions on the terminal and presses the submit button upon completion. The terminal then sends the collected response data to the server.

[0492] Step 2:

[0493] IoT sensors automatically detect residents' location and activity information. The device receives this data from the sensor and transfers it to the server.

[0494] Step 3:

[0495] The server collects relevant information through social media APIs that residents have previously authorized. The server stores the collected data in an internal database.

[0496] Step 4:

[0497] The server integrates and analyzes survey data, behavioral data, and social media data. Using this data, the server generates digital profiles of residents.

[0498] Step 5:

[0499] Based on the generated digital profile, the server uses a generator AI to create an avatar that possesses the residents' thought patterns and behavioral characteristics.

[0500] Step 6:

[0501] The server runs simulations using avatars on a digital twin. Through these simulations, the server evaluates the effectiveness of proposed urban planning solutions.

[0502] Step 7:

[0503] The server analyzes the simulation results and generates information necessary for urban planning. This generated information is then compiled into a resource that helps improve urban planning.

[0504] Step 8:

[0505] The server calculates the amount of local currency that should be awarded to each user based on the data provided.

[0506] Step 9:

[0507] The server assigns the calculated local currency to the user's account. The terminal displays a notification to the user regarding the received local currency.

[0508] (Example 1)

[0509] 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."

[0510] In modern urban development, there is a need to reflect the diverse opinions of residents and formulate precise regional plans. However, traditional methods fail to adequately model residents' activities and ideas, making it difficult to create urban plans that reflect their actual lifestyles. Furthermore, there is insufficient incentive provision for residents, and mechanisms to elicit cooperation in providing data are lacking.

[0511] 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.

[0512] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detection device for collecting residents' behavioral data, and means for collecting publicly available data to which residents have consented. This makes it possible to formulate precise regional plans that reflect the thinking patterns of residents.

[0513] "Residents" refers to individuals or groups living in a city or region, and are the providers of survey responses and behavioral data.

[0514] "Opinion data" refers to information about the thoughts and wishes expressed by residents through surveys and feedback.

[0515] "Behavioral data" refers to information about residents' daily movements and activities, and is acquired by detection devices.

[0516] A "detection device" refers to hardware used to sense residents' behavior and the environment and collect data.

[0517] "Public data" refers to information about statements and activity history that residents have made public on social media, etc.

[0518] "Digital information" refers to digitized profiles of residents generated by analyzing their opinion data, behavioral data, and publicly available data.

[0519] "Virtual representation" refers to digital characters and models generated based on the digital information of residents.

[0520] A "virtual environment" refers to a 3D or simulated space created on a computer, and is used in urban planning simulations.

[0521] "Simulation" is a process of conducting experiments using virtual representations within a virtual environment to evaluate the effectiveness of urban planning.

[0522] "Rewards" refer to local currency or perks given as incentives to residents for the data they provide.

[0523] A "local currency" is a unique currency that can be used within a specific region and is given to residents as a reward.

[0524] This invention is a system for formulating sophisticated urban development plans with the participation of residents. An embodiment of this system is described below.

[0525] This system first presents residents with a questionnaire via a terminal. The terminal has a graphical user interface (GUI) and provides a screen that is easy for residents to operate. Users can answer the presented questions using this terminal. This response data is securely transmitted to the server using encryption technology.

[0526] Next, the system utilizes IoT sensors to collect data on residents' daily activities. This consists of GPS modules for acquiring location information and motion sensors for detecting specific activities. The collected data is transmitted to a server via the terminal. The server integrates and centrally manages this data in a cloud environment.

[0527] Furthermore, the server will only collect residents' public statements and activity history through social media APIs if the residents consent. Access control will be implemented during this process to protect data privacy.

[0528] The server analyzes all the collected data and generates digital profiles of the residents. This analysis uses a generative AI model to obtain profiles that reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars that mimic the residents' thoughts and behaviors.

[0529] This avatar is used to perform simulations within a virtual environment called a digital twin. A digital twin is a virtual space that precisely replicates a real city and is used to evaluate urban planning proposals. Through this simulation, the server analyzes the social impact and effectiveness of the proposed plan.

[0530] Furthermore, the server provides local currency as a reward to residents. This is calculated based on the amount of data residents provide and is credited to the user's account. The terminal displays a notification of receipt of the local currency, informing residents of the result and providing an incentive for further data provision.

[0531] For example, when establishing a new sports facility in a city, the server can analyze residents' movement data and survey results to simulate the facility's placement on a digital twin. Based on these results, it can help to evaluate the impact the sports facility will have on the local community and develop a more appropriate plan.

[0532] An example of a prompt message for a generated AI model is: "Based on residents' opinions and behavioral data, simulate the impact of a new commercial facility and suggest its location."

[0533] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0534] Step 1:

[0535] The terminal presents the user with a questionnaire received from the server. Input is the questionnaire data sent from the server, and output is the questionnaire screen displayed to the user. The terminal utilizes a graphical user interface to create an environment where the user can comfortably input their answers. The user inputs their answers to the presented questions.

[0536] Step 2:

[0537] Once the user has finished entering their answers to the survey, the device sends that data to the server. The input is the user's response data, and the output is encrypted response data sent to the server. The device uses a secure protocol to transmit the data in order to maintain its confidentiality.

[0538] Step 3:

[0539] The server receives the collected response data and stores it in a database. The input is encrypted response data received from the terminal, and the output is the organized and stored response database. The server utilizes a database management system to prepare this data for analysis and performs data cleansing as needed.

[0540] Step 4:

[0541] The server receives daily behavioral data of residents collected by IoT sensors. The input is behavioral data sent from the sensors, and the output is a behavioral dataset organized for analysis. The server uses data mining techniques to extract patterns based on time and location information.

[0542] Step 5:

[0543] The server collects data through social media APIs with the permission of the users. The input is publicly available social media data, and the output is a usable feedback dataset. The server filters posts and activity history through API calls, obtaining the necessary information while respecting privacy.

[0544] Step 6:

[0545] The server integrates these different datasets to generate digital profiles of residents. The input is integrated information from response data, behavioral data, and social media data, and the output is the digital profile of each resident. A generative AI model is used to analyze this data and create profiles that reflect the residents' thought patterns and behavioral characteristics.

[0546] Step 7:

[0547] The server generates avatars based on digital profiles. The input is the resident's digital profile, and the output is an avatar usable in the virtual environment. This avatar is designed to simulate the resident's characteristics.

[0548] Step 8:

[0549] The server runs a simulation using avatars on a digital twin. The input is the initial settings for the avatars and digital twin, and the output is the simulation result data. The simulation is conducted based on a specific urban planning proposal, and data is collected to evaluate its impact.

[0550] Step 9:

[0551] The server analyzes the simulation results and generates urban planning information. The input is the result data obtained from the simulation, and the output is optimized design information for the proposed plan. The server uses this information to adjust parameters and create new proposals.

[0552] Step 10:

[0553] The server awards local currency to residents as compensation for providing data. The input is the amount of data and the value of the transactions provided by the residents, and the output is information about the awarded local currency. The terminal displays notifications to the user regarding the acquired currency, encouraging them to provide further data.

[0554] (Application Example 1)

[0555] 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."

[0556] Improving work efficiency and safety within factories is essential for economically sustainable operations. However, conventional methods do not adequately optimize worker movement, resulting in unnecessary travel and decreased productivity. Furthermore, there is a lack of appropriate incentives for data providers, making them less motivated to cooperate.

[0557] 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.

[0558] In this invention, the server includes means for managing survey data collected from residents, means for connecting residents' behavioral data to sensors, and means for collecting social media data to which residents have consented. This makes it possible to collect movement data of factory workers and propose optimized movement routes based on their digital profiles. Furthermore, it enhances motivation for cooperation by appropriately awarding virtual currency as a reward based on the provided data.

[0559] "Survey data" refers to data on opinions and desires collected from individuals or groups, and is used to gather information for a specific purpose.

[0560] "Behavioral data" refers to data collected using sensors and other means to understand a person's movements and activities, and is used to understand that person's behavioral patterns.

[0561] A "sensor" is a device that detects physical or environmental changes in order to acquire specific information, and is used for data collection.

[0562] "Social media data" refers to data related to information and statements that individuals post on online platforms, and serves as material for understanding individuals' interests and thoughts.

[0563] A "digital profile" refers to a digital representation of an individual's characteristics and behaviors, generated by analyzing collected data, and serves as the basis for mimicking an individual's features.

[0564] An "avatar" is a data model that simulates the thoughts and actions of an individual in the real world, generated based on a digital profile.

[0565] "Digital space" refers to a computer environment that virtually reproduces the real world and is used for virtualization processing and simulations.

[0566] "Virtualization processing" is a process that involves operating avatars in a digital space to simulate specific scenarios, and is used for solving problems in the real world.

[0567] "Environmental design" refers to design work planned to improve the efficiency and usability of physical or digital spaces.

[0568] "Motion data" refers to data that shows how individuals or devices are operating, and is used to optimize movement patterns.

[0569] "Cryptocurrency" is a type of currency traded digitally, which functions as an incentive and is offered as a reward.

[0570] A "user interface" refers to the point of contact between a system and a human being, designed to make it easy for the user to input information and view results.

[0571] "Notification" refers to the act or means of informing the parties of the outcome according to predetermined conditions.

[0572] The system that realizes this application integrates numerous devices and technologies to improve operational efficiency within the factory. The program operates through the steps of data collection, analysis, simulation in a virtual space, optimization suggestions, and incentive provision.

[0573] The server first collects real-time motion data of workers and equipment using sensor devices placed throughout the factory. This data is recorded based on location and time. XYZ sensors are used as the sensor devices, and communication is conducted using the MQTT protocol.

[0574] Next, the server uses Python data analysis libraries (e.g., Pandas, NumPy) to analyze the collected data in detail and generate digital profiles. This clarifies the behavioral patterns of individual workers and equipment. These profiles are used to generate avatars, which operate in a digital space built using Unity.

[0575] In the digital space, a server performs virtualization processing and simulates the avatar's movements. Through this simulation, it is possible to propose the optimal work route based on motion data. This result is provided to the worker via a user interface.

[0576] Users can receive suggestions on their smartphones and other devices to improve their work efficiency. In return for cooperating by providing data, the server will reward them with cryptocurrency and notify them of the reward results.

[0577] As a concrete example, in a food manufacturing plant, there are numerous work processes. By having the system suggest the optimal route for workers to move efficiently along the production line, unnecessary movements can be reduced and production efficiency can be increased.

[0578] Examples of prompts for a generative AI model are as follows:

[0579] "To optimize workflow within the factory, please analyze current worker movement data and calculate the optimal route."

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

[0581] Step 1:

[0582] The server collects motion data from sensor devices placed throughout the factory. As input, location and time data for each worker and piece of equipment are acquired in real time from the sensor devices (e.g., XYZ sensors). As output, this data is aggregated on the server and stored in a temporary database. The MQTT protocol is used for communication between the sensor devices and the server.

[0583] Step 2:

[0584] The server analyzes the collected motion data using Python data analysis libraries (Pandas, NumPy). The input is the motion data collected in step 1. The server processes the data and extracts the behavioral patterns of workers and equipment. The output is a digital profile containing the behavioral patterns of each individual. This profile is used in subsequent simulation processing.

[0585] Step 3:

[0586] The server generates an avatar in a digital space built using Unity, based on the generated digital profile. The digital profile obtained in step 2 is used as input. The output is the avatar being placed in the virtual environment and becoming executable. Specifically, the server incorporates the profile data into a Unity script and sets up actions corresponding to the avatar.

[0587] Step 4:

[0588] The server simulates the avatar's movements within the virtual space. As input, the avatar prepared in step 3 operates within the virtual space. Based on the movement data, the server analyzes the worker's movements by simulating multiple scenarios. As output, optimal movement paths and improvement suggestions are generated. These results are provided to the user in the next step.

[0589] Step 5:

[0590] The server notifies the user of the optimized workflow suggestion. The optimized workflow obtained in step 4 is used as input. As output, a notification is sent to a device such as a smartphone, allowing the worker to check the workflow in real time and follow the instructions. Specifically, the information is displayed on the user interface through the notification system.

[0591] Step 6:

[0592] The server distributes cryptocurrency as a reward for providing data. The input is the quantity and quality of the exercise data initially collected, which serve as evaluation criteria. The output is the distribution of rewards, with the cryptocurrency added to the user's account. Specifically, the server applies a reward calculation algorithm and notifies the user of the results through a notification system.

[0593] 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.

[0594] This invention is a system that incorporates an emotion engine into the system to analyze residents' emotional data in real time and continuously, and reflect this data in urban planning. This makes it possible to formulate more appropriate urban plans that take residents' emotions into consideration.

[0595] First, the device displays a questionnaire to residents, and users respond, sending their answers in a format that also includes emotional data. The device then transfers this questionnaire data to a server.

[0596] Next, IoT sensors and emotion engines installed in the devices detect and analyze residents' daily behavioral data and the physiological changes that occur during those activities. For example, this involves using cameras to read facial expressions and analyzing changes in voice tone from audio. This data is also collected on a server and incorporated as part of the residents' digital profiles.

[0597] The server receives the data analysis results from the emotion engine and integrates them with residents' behavioral data and survey results. This generates a digital profile that more precisely reflects the residents' thought patterns and emotional characteristics. Based on the generated profile, the server creates an avatar that takes the residents' emotions into account.

[0598] This avatar is used in a simulation within a digital twin to evaluate how emotional changes affect urban planning. The server analyzes the simulation results and generates information useful for developing urban plans that take emotional data into account.

[0599] Furthermore, the server awards local currency based on the data provided by residents. The provision of emotional data is also included in the evaluation, and appropriate incentives are provided. The terminal notifies residents of this, encouraging their active participation in future data provision.

[0600] For example, when considering the introduction of a new transportation system in a community, the server uses data, including changes in residents' emotions, to perform simulations. By evaluating the predicted increases in stress and satisfaction through emotional data, it becomes possible to analyze the social impact of the introduction in more detail and consider the optimal implementation method.

[0601] Thus, the present invention provides a system that supports highly accurate urban planning that takes emotional data into consideration, and can contribute to improving resident satisfaction.

[0602] The following describes the processing flow.

[0603] Step 1:

[0604] The terminal displays a questionnaire to residents. Users answer the questionnaire and input data, including questions related to emotions. The terminal sends the response data to the server.

[0605] Step 2:

[0606] IoT sensors and an emotion engine built into the device collect behavioral and physiological data from residents' daily activities. For example, cameras and microphones are used to analyze residents' emotions from their facial expressions and voices. The device then transfers this data to a server.

[0607] Step 3:

[0608] The server integrates survey data, sentiment data, and behavioral data to generate digital profiles for each resident. Here, the analysis data from the sentiment engine plays a crucial role.

[0609] Step 4:

[0610] The server creates an avatar that reflects the thoughts and feelings of the resident based on the generated digital profile. This avatar is designed to reflect the user's personality while also mimicking their emotional responses.

[0611] Step 5:

[0612] The server runs simulations on a digital twin. Through avatars, it tests different urban planning scenarios, including the impact of emotions. The server analyzes the changes in residents' emotions in each scenario.

[0613] Step 6:

[0614] The server generates urban planning information, including emotional data, based on simulation results, and then evaluates and optimizes it. This information is used to formulate plans that take into account the emotional needs of residents.

[0615] Step 7:

[0616] The server awards local currency based on data and sentiment information provided by residents. The terminal sends a notification to the user regarding the currency award and prompts them to provide data again.

[0617] Through this processing flow, it is possible to effectively utilize emotional data and formulate high-quality urban plans.

[0618] (Example 2)

[0619] 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."

[0620] In modern urban planning, the feelings and opinions of residents are often not adequately considered, leading to resident dissatisfaction and inappropriate urban environments. This problem stems from the fact that traditional survey methods make it difficult to grasp the deep-seated feelings and characteristics of residents, thus hindering qualitative improvements in urban planning. Furthermore, the lack of effective incentives to gain resident cooperation is another challenge.

[0621] 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.

[0622] In this invention, the server includes means for managing information data collected from residents, means for connecting to an observation device for collecting residents' behavioral data, and means for collecting information source data to which residents have consented. This enables highly accurate urban planning that takes residents' emotions into account by generating and applying digital features based on residents' emotional data. Furthermore, providing local resources as an incentive can encourage active participation from residents.

[0623] "Information data" refers to all data collected from residents, including opinions and feelings, and includes information from surveys and social media.

[0624] "Observation equipment" refers to devices used to detect residents' movements and physiological changes, including cameras and microphones. The data collected is then used for emotional analysis of residents.

[0625] "Source data" refers to data collected with the consent of residents and includes data from social media and other public information infrastructure.

[0626] "Digital features" are virtual profiles that represent the emotions and behavioral characteristics of residents, generated based on collected information data and data obtained from observation devices.

[0627] A "virtual entity" is an avatar generated based on digital characteristics, referring to a digital being that mimics the emotions and behavioral patterns of residents.

[0628] A "digital environment" refers to a simulation space where simulated experiments are conducted based on virtual entities, and is used to evaluate the impact of urban planning in advance.

[0629] A "simulated experiment" refers to the process of evaluating the impact of urban planning scenarios on residents by operating virtual entities within a digital environment.

[0630] "Urban planning" refers to a plan for the ideal form of a city and the placement of facilities that better meets the needs of residents, based on emotional data and the results of simulated experiments.

[0631] "Local resources" refer to resources that have value as rewards based on data provided by residents, and include local currencies and points.

[0632] The objective of this invention is to provide a system that supports highly accurate urban planning based on residents' emotional data. The system primarily operates through the cooperation of a server, terminals, and users, systematically collecting and analyzing residents' emotional data.

[0633] The server manages residents' informational and behavioral data, and generates digital characteristics based on this data. The analysis engine within the server makes full use of various data collection methods to form digital characteristics that reflect the thought patterns and emotional traits of each individual resident. This involves observation devices to monitor residents' daily behavior and data sources obtained with the residents' consent.

[0634] The terminal displays a survey for residents and sends the results to a server. The survey includes questions designed to reflect residents' emotions, allowing for detailed collection of their opinions. In addition, the terminal has a built-in camera and microphone, which sense changes in facial expressions and voice, and transmit this emotion data to the server.

[0635] Users provide their emotional state through their devices by answering questionnaires. The data collected through user participation is used for analysis on the server and evaluated as a candidate for regional resource allocation.

[0636] Specifically, when developing urban planning for the construction of new public facilities based on residents' sentiment data, the server first generates digital characteristics by integrating survey data and behavioral data from residents, and then derives optimal placement and design proposals based on the results.

[0637] An example of a prompt is, "Please tell me how to formulate an urban plan that takes into account residents' sentiment data when constructing a new public facility in a certain area." By inputting this prompt into the generating AI model, it will be supported in generating urban planning proposals that are more in line with the needs of residents.

[0638] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0639] Step 1:

[0640] The terminal displays a questionnaire to residents. The questionnaire includes questions that ask about residents' current feelings and opinions. When users answer the questionnaire, input data is generated. The terminal collects this input data and sends it to the server. The server classifies the received questionnaire data according to its content and stores it in a database.

[0641] Step 2:

[0642] The device uses its built-in camera and microphone to detect changes in residents' facial expressions and voices. As users perform their daily activities, these sensors acquire facial expression and voice data. Based on the acquired data, the emotion engine analyzes the data using image and voice analysis algorithms. The analysis results are output as emotion parameters and sent to the server.

[0643] Step 3:

[0644] The server integrates survey data and sentiment data received from terminals. Using data mining techniques, the server models residents' thought patterns and emotional characteristics. During this process, various data are processed using feature extraction and output as integrated digital features. The server stores these generated digital features in a database.

[0645] Step 4:

[0646] The server generates avatars that mimic the emotions of the residents based on the generated digital features. A generative AI model is used, and the avatar's parameters are set based on the input digital features. The output avatars are saved in preparation for simulation in a digital twin environment.

[0647] Step 5:

[0648] The server conducts simulated experiments using generated avatars in a digital twin environment. The simulation evaluates the impact of various urban planning scenarios on the avatars. The output of this simulation serves as a guideline for improving urban planning, taking emotional data into consideration.

[0649] Step 6:

[0650] The server analyzes the simulation results and extracts information on urban planning. The information obtained from the analysis is used to support local government decision-making. The server documents this information and provides it to the relevant departments through an interface.

[0651] Step 7:

[0652] The server provides residents with local resources as an incentive for providing data. The incentive is calculated based on the amount and value of the data provided by the resident. The terminal receives the calculation result and notifies the user, encouraging participation in future data provision.

[0653] (Application Example 2)

[0654] 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."

[0655] In modern urban environments, there is a growing need to utilize residents' emotional data to optimize urban design and commercial spaces. However, conventional methods of collecting emotional data are fragmented and fail to fundamentally improve residents' satisfaction. To solve this problem, a system is needed that can analyze residents' emotions in real time and quickly reflect appropriate measures based on that analysis.

[0656] 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.

[0657] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detector for collecting residents' activity data, and means for analyzing customers' physiological changes with an image capture device and extracting emotional data. This enables high-precision collection and analysis of residents' emotional data, allowing for rapid feedback for urban design and optimization of commercial spaces.

[0658] "Opinion data" refers to information that reflects an individual's thoughts and perceptions, based on surveys and feedback collected from residents.

[0659] "Activity data" refers to information about residents' daily actions and travel routes, which is collected by detectors.

[0660] "Online platform data" refers to information about social media and web activities that are provided with the consent of residents.

[0661] "Digital characteristics" refer to data that indicates the characteristics and tendencies of residents, generated by analyzing their opinion data and activity data.

[0662] A "virtual space" is a virtual environment based on the digital characteristics of residents simulated on a computer.

[0663] A "simulated experiment" is a simulation that observes the movements and reactions of avatars in a virtual space based on the digital characteristics of the residents, and analyzes the results.

[0664] An "image capture device" is a device, such as a camera or sensor, that captures and analyzes the facial expressions and movements of residents and customers.

[0665] "Emotional data" refers to data that indicates the emotional state extracted by analyzing the physiological changes of residents based on information obtained from image capture devices.

[0666] "Rewards" refer to local currency or other incentives given to residents for the information they provide.

[0667] The system used to realize this application involves collecting residents' emotional data with high accuracy and providing rapid feedback for urban design and the optimization of commercial spaces.

[0668] The server manages opinion data obtained from residents and collects activity data and physiological changes using IoT sensors and image capture devices. Terminals connected to the server, for example, capture customers' facial expressions in real time using cameras mounted on smart glasses and collect data to generate digital characteristics. OpenCV is used as the image processing software, and AWS or Google Cloud is used as the cloud solution.

[0669] Emotional data collected by the terminal is analyzed by a generative AI model in the cloud and sent to a server. The server uses this data to prepare real-time responses to residents and customers. An example of a prompt message would be, "Start facial analysis the moment the customer picks up the product, send the data to the server, and display the most appropriate customer service response on the glasses in real time." In this way, the present invention can provide a highly accurate urban planning support system that takes residents' emotional data into account, thereby contributing to improved resident satisfaction.

[0670] For example, imagine a scenario in a commercial facility where a store employee wearing smart glasses interacts with a customer, and the customer's emotional state is fed back to the employee in real time via the glasses' display. This allows the employee to tailor their service to each individual customer's emotions, thereby improving the customer experience.

[0671] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0672] Step 1:

[0673] The smart glasses within the device capture the customer's face and acquire image data in real time. The input is video from the camera built into the glasses, and the output is image data as a still image or video. This data is used as initial input for image processing.

[0674] Step 2:

[0675] The device analyzes the acquired image data using OpenCV to extract feature points from the customer's face. This process generates digital information representing subtle facial movements and expressions. The input is the image data obtained in step 1, and the output is numerical data including facial feature points.

[0676] Step 3:

[0677] The device uses feature points obtained through image processing to determine the emotional state. It utilizes a generative AI model to map feature points to emotional labels. The input is facial feature data, and the output is a label indicating the emotional state (e.g., joy, anger, surprise, etc.).

[0678] Step 4:

[0679] The determined emotional state is sent to a server connected to the cloud. The server receives this data, analyzes it, and uses it to generate information relevant to commercial activities. The input is the emotional state label, and the output is the initial dataset used for analysis.

[0680] Step 5:

[0681] The server uses a generative AI model to analyze emotional state data. It generates appropriate customer service methods and business strategies, taking into account real-time responses to customers. The input is the dataset obtained in step 4, and the output is optimized customer service instructions and strategies.

[0682] Step 6:

[0683] The generated customer service instructions and strategies are displayed on the smart glasses. The staff receive the instructions on the display and use them to interact with customers. The input is customer service instructions from the server, and the output is visual information for the staff.

[0684] Step 7:

[0685] Users respond to customers based on information displayed on their glasses and incorporate the results into their daily work. User feedback is also used to improve the next data collection and analysis process. The input is the information displayed on the glasses' screen, and the output is customer satisfaction and commercial results.

[0686] 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.

[0687] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0688] 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.

[0689] [Fourth Embodiment]

[0690] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0691] 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.

[0692] 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).

[0693] 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.

[0694] 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.

[0695] 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).

[0696] 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.

[0697] 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.

[0698] 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.

[0699] 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.

[0700] 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.

[0701] 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.

[0702] 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".

[0703] This invention is a system for formulating highly accurate urban plans using resident data, and includes the following functions.

[0704] First, a questionnaire is presented to residents via a device. Users answer the questions presented through the device, and these answers are sent from the device to the server. At this stage, data regarding residents' personal opinions and wishes is collected.

[0705] Next, IoT sensors are used to automatically acquire data on residents' daily activities. The acquired activity data is transferred to a server via a terminal. During this process, location information and residents' movements at specific times are recorded.

[0706] Furthermore, the server collects social media data to the extent permitted by the residents. This is done via the APIs of social media platforms, making it possible to obtain residents' public statements and activity history.

[0707] This data is integrated and analyzed on a server to generate digital profiles of residents. These digital profiles reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars. These avatars mimic the residents' thoughts and behaviors and are used in simulations on the digital twin.

[0708] A digital twin is a virtual environment that recreates a real city in a virtual space, and is used to run simulations using avatars. The server evaluates the effectiveness of urban planning proposals through simulations, analyzes the obtained data, and derives the optimal urban design.

[0709] In this process, residents are offered local currency as a reward for cooperating by providing data. The server calculates the local currency based on the data provided and adds it to the user's account. The terminal displays a notification to the user that they have received the local currency, playing a role in encouraging residents to provide further data.

[0710] For example, when considering the establishment of a new park in a city, the server analyzes resident movement data and survey results, and runs a simulation of the park's placement on a digital twin. Based on these results, it becomes possible to concretely understand the social value and impact that the park would bring and to formulate an appropriate plan.

[0711] Thus, the present invention provides a system that makes it possible to improve the accuracy of urban planning through resident-participatory data collection and analysis.

[0712] The following describes the processing flow.

[0713] Step 1:

[0714] The terminal presents a questionnaire to the resident. The user answers the questions on the terminal and presses the submit button upon completion. The terminal then sends the collected response data to the server.

[0715] Step 2:

[0716] IoT sensors automatically detect residents' location and activity information. The device receives this data from the sensor and transfers it to the server.

[0717] Step 3:

[0718] The server collects relevant information through social media APIs that residents have previously authorized. The server stores the collected data in an internal database.

[0719] Step 4:

[0720] The server integrates and analyzes survey data, behavioral data, and social media data. Using this data, the server generates digital profiles of residents.

[0721] Step 5:

[0722] Based on the generated digital profile, the server uses a generator AI to create an avatar that possesses the residents' thought patterns and behavioral characteristics.

[0723] Step 6:

[0724] The server runs simulations using avatars on a digital twin. Through these simulations, the server evaluates the effectiveness of proposed urban planning solutions.

[0725] Step 7:

[0726] The server analyzes the simulation results and generates information necessary for urban planning. This generated information is then compiled into a resource that helps improve urban planning.

[0727] Step 8:

[0728] The server calculates the amount of local currency that should be awarded to each user based on the data provided.

[0729] Step 9:

[0730] The server assigns the calculated local currency to the user's account. The terminal displays a notification to the user regarding the received local currency.

[0731] (Example 1)

[0732] 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".

[0733] In modern urban development, there is a need to reflect the diverse opinions of residents and formulate precise regional plans. However, traditional methods fail to adequately model residents' activities and ideas, making it difficult to create urban plans that reflect their actual lifestyles. Furthermore, there is insufficient incentive provision for residents, and mechanisms to elicit cooperation in providing data are lacking.

[0734] 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.

[0735] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detection device for collecting residents' behavioral data, and means for collecting publicly available data to which residents have consented. This makes it possible to formulate precise regional plans that reflect the thinking patterns of residents.

[0736] "Residents" refers to individuals or groups living in a city or region, and are the providers of survey responses and behavioral data.

[0737] "Opinion data" refers to information about the thoughts and wishes expressed by residents through surveys and feedback.

[0738] "Behavioral data" refers to information about residents' daily movements and activities, and is acquired by detection devices.

[0739] A "detection device" refers to hardware used to sense residents' behavior and the environment and collect data.

[0740] "Public data" refers to information about statements and activity history that residents have made public on social media, etc.

[0741] "Digital information" refers to digitized profiles of residents generated by analyzing their opinion data, behavioral data, and publicly available data.

[0742] "Virtual representation" refers to digital characters and models generated based on the digital information of residents.

[0743] A "virtual environment" refers to a 3D or simulated space created on a computer, and is used in urban planning simulations.

[0744] "Simulation" is a process of conducting experiments using virtual representations within a virtual environment to evaluate the effectiveness of urban planning.

[0745] "Rewards" refer to local currency or perks given as incentives to residents for the data they provide.

[0746] A "local currency" is a unique currency that can be used within a specific region and is given to residents as a reward.

[0747] This invention is a system for formulating sophisticated urban development plans with the participation of residents. An embodiment of this system is described below.

[0748] This system first presents residents with a questionnaire via a terminal. The terminal has a graphical user interface (GUI) and provides a screen that is easy for residents to operate. Users can answer the presented questions using this terminal. This response data is securely transmitted to the server using encryption technology.

[0749] Next, the system utilizes IoT sensors to collect data on residents' daily activities. This consists of GPS modules for acquiring location information and motion sensors for detecting specific activities. The collected data is transmitted to a server via the terminal. The server integrates and centrally manages this data in a cloud environment.

[0750] Furthermore, the server will only collect residents' public statements and activity history through social media APIs if the residents consent. Access control will be implemented during this process to protect data privacy.

[0751] The server analyzes all the collected data and generates digital profiles of the residents. This analysis uses a generative AI model to obtain profiles that reflect the residents' thought patterns and behavioral characteristics. Based on these profiles, the server generates avatars that mimic the residents' thoughts and behaviors.

[0752] This avatar is used to perform simulations within a virtual environment called a digital twin. A digital twin is a virtual space that precisely replicates a real city and is used to evaluate urban planning proposals. Through this simulation, the server analyzes the social impact and effectiveness of the proposed plan.

[0753] Furthermore, the server provides local currency as a reward to residents. This is calculated based on the amount of data residents provide and is credited to the user's account. The terminal displays a notification of receipt of the local currency, informing residents of the result and providing an incentive for further data provision.

[0754] For example, when establishing a new sports facility in a city, the server can analyze residents' movement data and survey results to simulate the facility's placement on a digital twin. Based on these results, it can help to evaluate the impact the sports facility will have on the local community and develop a more appropriate plan.

[0755] An example of a prompt message for a generated AI model is: "Based on residents' opinions and behavioral data, simulate the impact of a new commercial facility and suggest its location."

[0756] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0757] Step 1:

[0758] The terminal presents the user with a questionnaire received from the server. Input is the questionnaire data sent from the server, and output is the questionnaire screen displayed to the user. The terminal utilizes a graphical user interface to create an environment where the user can comfortably input their answers. The user inputs their answers to the presented questions.

[0759] Step 2:

[0760] Once the user has finished entering their answers to the survey, the device sends that data to the server. The input is the user's response data, and the output is encrypted response data sent to the server. The device uses a secure protocol to transmit the data in order to maintain its confidentiality.

[0761] Step 3:

[0762] The server receives the collected response data and stores it in a database. The input is encrypted response data received from the terminal, and the output is the organized and stored response database. The server utilizes a database management system to prepare this data for analysis and performs data cleansing as needed.

[0763] Step 4:

[0764] The server receives daily behavioral data of residents collected by IoT sensors. The input is behavioral data sent from the sensors, and the output is a behavioral dataset organized for analysis. The server uses data mining techniques to extract patterns based on time and location information.

[0765] Step 5:

[0766] The server collects data through social media APIs with the permission of the users. The input is publicly available social media data, and the output is a usable feedback dataset. The server filters posts and activity history through API calls, obtaining the necessary information while respecting privacy.

[0767] Step 6:

[0768] The server integrates these different datasets to generate digital profiles of residents. The input is integrated information from response data, behavioral data, and social media data, and the output is the digital profile of each resident. A generative AI model is used to analyze this data and create profiles that reflect the residents' thought patterns and behavioral characteristics.

[0769] Step 7:

[0770] The server generates avatars based on digital profiles. The input is the resident's digital profile, and the output is an avatar usable in the virtual environment. This avatar is designed to simulate the resident's characteristics.

[0771] Step 8:

[0772] The server runs a simulation using avatars on a digital twin. The input is the initial settings for the avatars and digital twin, and the output is the simulation result data. The simulation is conducted based on a specific urban planning proposal, and data is collected to evaluate its impact.

[0773] Step 9:

[0774] The server analyzes the simulation results and generates urban planning information. The input is the result data obtained from the simulation, and the output is optimized design information for the proposed plan. The server uses this information to adjust parameters and create new proposals.

[0775] Step 10:

[0776] The server awards local currency to residents as compensation for providing data. The input is the amount of data and the value of the transactions provided by the residents, and the output is information about the awarded local currency. The terminal displays notifications to the user regarding the acquired currency, encouraging them to provide further data.

[0777] (Application Example 1)

[0778] 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".

[0779] Improving work efficiency and safety within factories is essential for economically sustainable operations. However, conventional methods do not adequately optimize worker movement, resulting in unnecessary travel and decreased productivity. Furthermore, there is a lack of appropriate incentives for data providers, making them less motivated to cooperate.

[0780] 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.

[0781] In this invention, the server includes means for managing survey data collected from residents, means for connecting residents' behavioral data to sensors, and means for collecting social media data to which residents have consented. This makes it possible to collect movement data of factory workers and propose optimized movement routes based on their digital profiles. Furthermore, it enhances motivation for cooperation by appropriately awarding virtual currency as a reward based on the provided data.

[0782] "Survey data" refers to data on opinions and desires collected from individuals or groups, and is used to gather information for a specific purpose.

[0783] "Behavioral data" refers to data collected using sensors and other means to understand a person's movements and activities, and is used to understand that person's behavioral patterns.

[0784] A "sensor" is a device that detects physical or environmental changes in order to acquire specific information, and is used for data collection.

[0785] "Social media data" refers to data related to information and statements that individuals post on online platforms, and serves as material for understanding individuals' interests and thoughts.

[0786] A "digital profile" refers to a digital representation of an individual's characteristics and behaviors, generated by analyzing collected data, and serves as the basis for mimicking an individual's features.

[0787] An "avatar" is a data model that simulates the thoughts and actions of an individual in the real world, generated based on a digital profile.

[0788] "Digital space" refers to a computer environment that virtually reproduces the real world and is used for virtualization processing and simulations.

[0789] "Virtualization processing" is a process that involves operating avatars in a digital space to simulate specific scenarios, and is used for solving problems in the real world.

[0790] "Environmental design" refers to design work planned to improve the efficiency and usability of physical or digital spaces.

[0791] "Motion data" refers to data that shows how individuals or devices are operating, and is used to optimize movement patterns.

[0792] "Cryptocurrency" is a type of currency traded digitally, which functions as an incentive and is offered as a reward.

[0793] A "user interface" refers to the point of contact between a system and a human being, designed to make it easy for the user to input information and view results.

[0794] "Notification" refers to the act or means of informing the parties of the outcome according to predetermined conditions.

[0795] The system that realizes this application integrates numerous devices and technologies to improve operational efficiency within the factory. The program operates through the steps of data collection, analysis, simulation in a virtual space, optimization suggestions, and incentive provision.

[0796] The server first collects real-time motion data of workers and equipment using sensor devices placed throughout the factory. This data is recorded based on location and time. XYZ sensors are used as the sensor devices, and communication is conducted using the MQTT protocol.

[0797] Next, the server uses Python data analysis libraries (e.g., Pandas, NumPy) to analyze the collected data in detail and generate digital profiles. This clarifies the behavioral patterns of individual workers and equipment. These profiles are used to generate avatars, which operate in a digital space built using Unity.

[0798] In the digital space, a server performs virtualization processing and simulates the avatar's movements. Through this simulation, it is possible to propose the optimal work route based on motion data. This result is provided to the worker via a user interface.

[0799] Users can receive suggestions on their smartphones and other devices to improve their work efficiency. In return for cooperating by providing data, the server will reward them with cryptocurrency and notify them of the reward results.

[0800] As a concrete example, in a food manufacturing plant, there are numerous work processes. By having the system suggest the optimal route for workers to move efficiently along the production line, unnecessary movements can be reduced and production efficiency can be increased.

[0801] Examples of prompts for a generative AI model are as follows:

[0802] "To optimize workflow within the factory, please analyze current worker movement data and calculate the optimal route."

[0803] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0804] Step 1:

[0805] The server collects motion data from sensor devices placed throughout the factory. As input, location and time data for each worker and piece of equipment are acquired in real time from the sensor devices (e.g., XYZ sensors). As output, this data is aggregated on the server and stored in a temporary database. The MQTT protocol is used for communication between the sensor devices and the server.

[0806] Step 2:

[0807] The server analyzes the collected motion data using Python data analysis libraries (Pandas, NumPy). The input is the motion data collected in step 1. The server processes the data and extracts the behavioral patterns of workers and equipment. The output is a digital profile containing the behavioral patterns of each individual. This profile is used in subsequent simulation processing.

[0808] Step 3:

[0809] The server generates an avatar in a digital space built using Unity, based on the generated digital profile. The digital profile obtained in step 2 is used as input. The output is the avatar being placed in the virtual environment and becoming executable. Specifically, the server incorporates the profile data into a Unity script and sets up actions corresponding to the avatar.

[0810] Step 4:

[0811] The server simulates the avatar's movements within the virtual space. As input, the avatar prepared in step 3 operates within the virtual space. Based on the movement data, the server analyzes the worker's movements by simulating multiple scenarios. As output, optimal movement paths and improvement suggestions are generated. These results are provided to the user in the next step.

[0812] Step 5:

[0813] The server notifies the user of the optimized workflow suggestion. The optimized workflow obtained in step 4 is used as input. As output, a notification is sent to a device such as a smartphone, allowing the worker to check the workflow in real time and follow the instructions. Specifically, the information is displayed on the user interface through the notification system.

[0814] Step 6:

[0815] The server distributes cryptocurrency as a reward for providing data. The input is the quantity and quality of the exercise data initially collected, which serve as evaluation criteria. The output is the distribution of rewards, with the cryptocurrency added to the user's account. Specifically, the server applies a reward calculation algorithm and notifies the user of the results through a notification system.

[0816] 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.

[0817] This invention is a system that incorporates an emotion engine into the system to analyze residents' emotional data in real time and continuously, and reflect this data in urban planning. This makes it possible to formulate more appropriate urban plans that take residents' emotions into consideration.

[0818] First, the device displays a questionnaire to residents, and users respond, sending their answers in a format that also includes emotional data. The device then transfers this questionnaire data to a server.

[0819] Next, IoT sensors and emotion engines installed in the devices detect and analyze residents' daily behavioral data and the physiological changes that occur during those activities. For example, this involves using cameras to read facial expressions and analyzing changes in voice tone from audio. This data is also collected on a server and incorporated as part of the residents' digital profiles.

[0820] The server receives the data analysis results from the emotion engine and integrates them with residents' behavioral data and survey results. This generates a digital profile that more precisely reflects the residents' thought patterns and emotional characteristics. Based on the generated profile, the server creates an avatar that takes the residents' emotions into account.

[0821] This avatar is used in a simulation within a digital twin to evaluate how emotional changes affect urban planning. The server analyzes the simulation results and generates information useful for developing urban plans that take emotional data into account.

[0822] Furthermore, the server awards local currency based on the data provided by residents. The provision of emotional data is also included in the evaluation, and appropriate incentives are provided. The terminal notifies residents of this, encouraging their active participation in future data provision.

[0823] For example, when considering the introduction of a new transportation system in a community, the server uses data, including changes in residents' emotions, to perform simulations. By evaluating the predicted increases in stress and satisfaction through emotional data, it becomes possible to analyze the social impact of the introduction in more detail and consider the optimal implementation method.

[0824] Thus, the present invention provides a system that supports highly accurate urban planning that takes emotional data into consideration, and can contribute to improving resident satisfaction.

[0825] The following describes the processing flow.

[0826] Step 1:

[0827] The terminal displays a questionnaire to residents. Users answer the questionnaire and input data, including questions related to emotions. The terminal sends the response data to the server.

[0828] Step 2:

[0829] IoT sensors and an emotion engine built into the device collect behavioral and physiological data from residents' daily activities. For example, cameras and microphones are used to analyze residents' emotions from their facial expressions and voices. The device then transfers this data to a server.

[0830] Step 3:

[0831] The server integrates survey data, sentiment data, and behavioral data to generate digital profiles for each resident. Here, the analysis data from the sentiment engine plays a crucial role.

[0832] Step 4:

[0833] The server creates an avatar that reflects the thoughts and feelings of the resident based on the generated digital profile. This avatar is designed to reflect the user's personality while also mimicking their emotional responses.

[0834] Step 5:

[0835] The server runs simulations on a digital twin. Through avatars, it tests different urban planning scenarios, including the impact of emotions. The server analyzes the changes in residents' emotions in each scenario.

[0836] Step 6:

[0837] The server generates urban planning information, including emotional data, based on simulation results, and then evaluates and optimizes it. This information is used to formulate plans that take into account the emotional needs of residents.

[0838] Step 7:

[0839] The server awards local currency based on data and sentiment information provided by residents. The terminal sends a notification to the user regarding the currency award and prompts them to provide data again.

[0840] Through this processing flow, it is possible to effectively utilize emotional data and formulate high-quality urban plans.

[0841] (Example 2)

[0842] 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".

[0843] In modern urban planning, the feelings and opinions of residents are often not adequately considered, leading to resident dissatisfaction and inappropriate urban environments. This problem stems from the fact that traditional survey methods make it difficult to grasp the deep-seated feelings and characteristics of residents, thus hindering qualitative improvements in urban planning. Furthermore, the lack of effective incentives to gain resident cooperation is another challenge.

[0844] 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.

[0845] In this invention, the server includes means for managing information data collected from residents, means for connecting to an observation device for collecting residents' behavioral data, and means for collecting information source data to which residents have consented. This enables highly accurate urban planning that takes residents' emotions into account by generating and applying digital features based on residents' emotional data. Furthermore, providing local resources as an incentive can encourage active participation from residents.

[0846] "Information data" refers to all data collected from residents, including opinions and feelings, and includes information from surveys and social media.

[0847] "Observation equipment" refers to devices used to detect residents' movements and physiological changes, including cameras and microphones. The data collected is then used for emotional analysis of residents.

[0848] "Source data" refers to data collected with the consent of residents and includes data from social media and other public information infrastructure.

[0849] "Digital features" are virtual profiles that represent the emotions and behavioral characteristics of residents, generated based on collected information data and data obtained from observation devices.

[0850] A "virtual entity" is an avatar generated based on digital characteristics, referring to a digital being that mimics the emotions and behavioral patterns of residents.

[0851] A "digital environment" refers to a simulation space where simulated experiments are conducted based on virtual entities, and is used to evaluate the impact of urban planning in advance.

[0852] A "simulated experiment" refers to the process of evaluating the impact of urban planning scenarios on residents by operating virtual entities within a digital environment.

[0853] "Urban planning" refers to a plan for the ideal form of a city and the placement of facilities that better meets the needs of residents, based on emotional data and the results of simulated experiments.

[0854] "Local resources" refer to resources that have value as rewards based on data provided by residents, and include local currencies and points.

[0855] The objective of this invention is to provide a system that supports highly accurate urban planning based on residents' emotional data. The system primarily operates through the cooperation of a server, terminals, and users, systematically collecting and analyzing residents' emotional data.

[0856] The server manages residents' informational and behavioral data, and generates digital characteristics based on this data. The analysis engine within the server makes full use of various data collection methods to form digital characteristics that reflect the thought patterns and emotional traits of each individual resident. This involves observation devices to monitor residents' daily behavior and data sources obtained with the residents' consent.

[0857] The terminal displays a survey for residents and sends the results to a server. The survey includes questions designed to reflect residents' emotions, allowing for detailed collection of their opinions. In addition, the terminal has a built-in camera and microphone, which sense changes in facial expressions and voice, and transmit this emotion data to the server.

[0858] Users provide their emotional state through their devices by answering questionnaires. The data collected through user participation is used for analysis on the server and evaluated as a candidate for regional resource allocation.

[0859] Specifically, when developing urban planning for the construction of new public facilities based on residents' sentiment data, the server first generates digital characteristics by integrating survey data and behavioral data from residents, and then derives optimal placement and design proposals based on the results.

[0860] An example of a prompt is, "Please tell me how to formulate an urban plan that takes into account residents' sentiment data when constructing a new public facility in a certain area." By inputting this prompt into the generating AI model, it will be supported in generating urban planning proposals that are more in line with the needs of residents.

[0861] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0862] Step 1:

[0863] The terminal displays a questionnaire to residents. The questionnaire includes questions that ask about residents' current feelings and opinions. When users answer the questionnaire, input data is generated. The terminal collects this input data and sends it to the server. The server classifies the received questionnaire data according to its content and stores it in a database.

[0864] Step 2:

[0865] The device uses its built-in camera and microphone to detect changes in residents' facial expressions and voices. As users perform their daily activities, these sensors acquire facial expression and voice data. Based on the acquired data, the emotion engine analyzes the data using image and voice analysis algorithms. The analysis results are output as emotion parameters and sent to the server.

[0866] Step 3:

[0867] The server integrates survey data and sentiment data received from terminals. Using data mining techniques, the server models residents' thought patterns and emotional characteristics. During this process, various data are processed using feature extraction and output as integrated digital features. The server stores these generated digital features in a database.

[0868] Step 4:

[0869] The server generates avatars that mimic the emotions of the residents based on the generated digital features. A generative AI model is used, and the avatar's parameters are set based on the input digital features. The output avatars are saved in preparation for simulation in a digital twin environment.

[0870] Step 5:

[0871] The server conducts simulated experiments using generated avatars in a digital twin environment. The simulation evaluates the impact of various urban planning scenarios on the avatars. The output of this simulation serves as a guideline for improving urban planning, taking emotional data into consideration.

[0872] Step 6:

[0873] The server analyzes the simulation results and extracts information on urban planning. The information obtained from the analysis is used to support local government decision-making. The server documents this information and provides it to the relevant departments through an interface.

[0874] Step 7:

[0875] The server provides residents with local resources as an incentive for providing data. The incentive is calculated based on the amount and value of the data provided by the resident. The terminal receives the calculation result and notifies the user, encouraging participation in future data provision.

[0876] (Application Example 2)

[0877] 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".

[0878] In modern urban environments, there is a growing need to utilize residents' emotional data to optimize urban design and commercial spaces. However, conventional methods of collecting emotional data are fragmented and fail to fundamentally improve residents' satisfaction. To solve this problem, a system is needed that can analyze residents' emotions in real time and quickly reflect appropriate measures based on that analysis.

[0879] 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.

[0880] In this invention, the server includes means for managing opinion data collected from residents, means for connecting to a detector for collecting residents' activity data, and means for analyzing customers' physiological changes with an image capture device and extracting emotional data. This enables high-precision collection and analysis of residents' emotional data, allowing for rapid feedback for urban design and optimization of commercial spaces.

[0881] "Opinion data" refers to information that reflects an individual's thoughts and perceptions, based on surveys and feedback collected from residents.

[0882] "Activity data" refers to information about residents' daily actions and travel routes, which is collected by detectors.

[0883] "Online platform data" refers to information about social media and web activities that are provided with the consent of residents.

[0884] "Digital characteristics" refer to data that indicates the characteristics and tendencies of residents, generated by analyzing their opinion data and activity data.

[0885] A "virtual space" is a virtual environment based on the digital characteristics of residents simulated on a computer.

[0886] A "simulated experiment" is a simulation that observes the movements and reactions of avatars in a virtual space based on the digital characteristics of the residents, and analyzes the results.

[0887] An "image capture device" is a device, such as a camera or sensor, that captures and analyzes the facial expressions and movements of residents and customers.

[0888] "Emotional data" refers to data that indicates the emotional state extracted by analyzing the physiological changes of residents based on information obtained from image capture devices.

[0889] "Rewards" refer to local currency or other incentives given to residents for the information they provide.

[0890] The system used to realize this application involves collecting residents' emotional data with high accuracy and providing rapid feedback for urban design and the optimization of commercial spaces.

[0891] The server manages opinion data obtained from residents and collects activity data and physiological changes using IoT sensors and image capture devices. Terminals connected to the server, for example, capture customers' facial expressions in real time using cameras mounted on smart glasses and collect data to generate digital characteristics. OpenCV is used as the image processing software, and AWS or Google Cloud is used as the cloud solution.

[0892] Emotional data collected by the terminal is analyzed by a generative AI model in the cloud and sent to a server. The server uses this data to prepare real-time responses to residents and customers. An example of a prompt message would be, "Start facial analysis the moment the customer picks up the product, send the data to the server, and display the most appropriate customer service response on the glasses in real time." In this way, the present invention can provide a highly accurate urban planning support system that takes residents' emotional data into account, thereby contributing to improved resident satisfaction.

[0893] For example, imagine a scenario in a commercial facility where a store employee wearing smart glasses interacts with a customer, and the customer's emotional state is fed back to the employee in real time via the glasses' display. This allows the employee to tailor their service to each individual customer's emotions, thereby improving the customer experience.

[0894] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0895] Step 1:

[0896] The smart glasses within the device capture the customer's face and acquire image data in real time. The input is video from the camera built into the glasses, and the output is image data as a still image or video. This data is used as initial input for image processing.

[0897] Step 2:

[0898] The device analyzes the acquired image data using OpenCV to extract feature points from the customer's face. This process generates digital information representing subtle facial movements and expressions. The input is the image data obtained in step 1, and the output is numerical data including facial feature points.

[0899] Step 3:

[0900] The device uses feature points obtained through image processing to determine the emotional state. It utilizes a generative AI model to map feature points to emotional labels. The input is facial feature data, and the output is a label indicating the emotional state (e.g., joy, anger, surprise, etc.).

[0901] Step 4:

[0902] The determined emotional state is sent to a server connected to the cloud. The server receives this data, analyzes it, and uses it to generate information relevant to commercial activities. The input is the emotional state label, and the output is the initial dataset used for analysis.

[0903] Step 5:

[0904] The server uses a generative AI model to analyze emotional state data. It generates appropriate customer service methods and business strategies, taking into account real-time responses to customers. The input is the dataset obtained in step 4, and the output is optimized customer service instructions and strategies.

[0905] Step 6:

[0906] The generated customer service instructions and strategies are displayed on the smart glasses. The staff receive the instructions on the display and use them to interact with customers. The input is customer service instructions from the server, and the output is visual information for the staff.

[0907] Step 7:

[0908] Users respond to customers based on information displayed on their glasses and incorporate the results into their daily work. User feedback is also used to improve the next data collection and analysis process. The input is the information displayed on the glasses' screen, and the output is customer satisfaction and commercial results.

[0909] 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.

[0910] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0911] 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.

[0912] 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.

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] 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."

[0918] 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.

[0919] 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.

[0920] 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.

[0921] 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.

[0922] 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.

[0923] 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.

[0924] 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.

[0925] 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.

[0926] 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.

[0927] 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.

[0928] 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.

[0929] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0930] The following is further disclosed regarding the embodiments described above.

[0931] (Claim 1)

[0932] A means of managing survey data collected from residents,

[0933] A means of connecting to sensors for collecting residents' behavioral data,

[0934] Means of collecting social media data with the consent of residents,

[0935] A means of analyzing this data and generating digital profiles of residents,

[0936] A means of generating an avatar that mimics the thought patterns of residents based on the generated digital profile,

[0937] A means for performing a simulation in which the aforementioned avatar operates on a digital twin,

[0938] A means of analyzing simulation results and generating urban planning information,

[0939] A means of providing local currency as an incentive based on data provided by residents,

[0940] A system that includes this.

[0941] (Claim 2)

[0942] The system according to claim 1, including an interface for providing urban planning information to a local government.

[0943] (Claim 3)

[0944] The system according to claim 1, comprising means for notifying residents of the results of the incentive grant.

[0945] "Example 1"

[0946] (Claim 1)

[0947] A means of managing opinion data collected from residents,

[0948] A means for connecting to a detection device for collecting residents' behavioral data,

[0949] Means of collecting publicly available data with the consent of residents,

[0950] A means of analyzing this data and generating digital information about residents,

[0951] A means for generating a virtual representation that mimics the thought patterns of residents based on the generated digital information,

[0952] A means for performing a simulation in which the aforementioned virtual representation operates in a virtual environment,

[0953] A means for analyzing simulation results and generating development plan information,

[0954] A means of providing local currency as a reward based on data provided by residents,

[0955] A system that includes this.

[0956] (Claim 2)

[0957] The system according to claim 1, including an operation screen for providing information on development plans to government agencies.

[0958] (Claim 3)

[0959] The system according to claim 1, comprising means for notifying residents of the results of the reward grant.

[0960] "Application Example 1"

[0961] (Claim 1)

[0962] A means of managing survey data collected from residents,

[0963] A means of connecting to sensors for collecting residents' behavioral data,

[0964] Means of collecting social media data with the consent of residents,

[0965] A means of analyzing this data and generating digital profiles of residents,

[0966] A means of generating an avatar that mimics the thought patterns of residents based on the generated digital profile,

[0967] Means for performing virtualization processing to operate the aforementioned avatar in a digital space,

[0968] A means for analyzing virtualization processing results and generating environment design information,

[0969] A means of collecting worker movement data and proposing optimized movement paths,

[0970] A means of awarding cryptocurrency as a reward based on the provided data,

[0971] A system that includes this.

[0972] (Claim 2)

[0973] The system according to claim 1, comprising a user interface for providing urban planning information.

[0974] (Claim 3)

[0975] The system according to claim 1, comprising means for notifying the result of the awarding of rewards.

[0976] "Example 2 of combining an emotion engine"

[0977] (Claim 1)

[0978] A means of managing information data collected from residents,

[0979] A means of connecting to an observation device for collecting residents' movement data,

[0980] Means of collecting source data with the consent of residents,

[0981] A means of analyzing this data to generate digital characteristics of residents,

[0982] A means for generating a virtual body that mimics the behavioral patterns of residents based on the generated digital features,

[0983] A means for performing a simulated experiment in which the aforementioned virtual entity operates in a digital environment,

[0984] A means of analyzing the results of a simulated experiment and generating information on urban planning,

[0985] A means of providing local resources as compensation based on data provided by residents,

[0986] A means of monitoring and analyzing physiological changes during data collection,

[0987] A means to support the optimization of urban planning that takes emotional data into consideration,

[0988] A system that includes this.

[0989] (Claim 2)

[0990] The system according to claim 1, comprising a connection device for providing information on urban planning to local administrative agencies.

[0991] (Claim 3)

[0992] The system according to claim 1, comprising means for notifying residents of the results of the reward grant.

[0993] "Application example 2 when combining with an emotional engine"

[0994] (Claim 1)

[0995] A means of managing opinion data collected from residents,

[0996] A means of connecting to a detector for collecting residents' activity data,

[0997] Means of collecting online platform data with the consent of residents,

[0998] A means of analyzing this information and generating the digital characteristics of residents,

[0999] A means of generating avatars that mimic the thought processes of residents based on the generated digital characteristics,

[1000] A means for conducting a simulated experiment in which the aforementioned avatar is operated in a virtual space,

[1001] A means of analyzing the results of a simulated experiment and generating information for urban planning,

[1002] A means of analyzing the physiological changes of customers using an image capture device and extracting emotional data,

[1003] A means of analyzing extracted emotional data and providing real-time responses to the target,

[1004] A means of providing local resources as compensation based on information provided by residents,

[1005] A system that includes this.

[1006] (Claim 2)

[1007] The system according to claim 1, comprising an interface for providing urban planning information to administrative agencies.

[1008] (Claim 3)

[1009] The system according to claim 1, including means for communicating the results of the reward grant to residents. [Explanation of symbols]

[1010] 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 means of managing survey data collected from residents, A means of connecting to sensors for collecting residents' behavioral data, Means of collecting social media data with the consent of residents, A means of analyzing this data and generating digital profiles of residents, A means of generating an avatar that mimics the thought patterns of residents based on the generated digital profile, A means for performing a simulation in which the aforementioned avatar operates on a digital twin, A means of analyzing simulation results and generating urban planning information, A means of providing local currency as an incentive based on data provided by residents, A system that includes this.

2. The system according to claim 1, including an interface for providing urban planning information to a local government.

3. The system according to claim 1, comprising means for notifying residents of the results of the incentive grant.

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