system

Abstract

We provide the system. [Solution] A means of receiving image data, audio data, and text data entered by an individual, A means of converting audio data into text data, A means for analyzing the aforementioned image data and text data and extracting characteristics of the living environment and lifestyle, A means of selecting a relocation destination that suits the user's needs, A means of presenting users with information about the selected relocation destination, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes 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] Currently, urban concentration is progressing, and accompanying problems such as soaring land prices and environmental degradation have become issues. On the other hand, in local areas, population decline and an increase in vacant houses are remarkable. Under such circumstances, it is difficult to find a relocation destination that is optimal for an individual's lifestyle and living costs, and it takes wasted time and labor. In addition, there is a problem that it is impossible to receive an appropriate proposal that satisfies a user's potential needs with only ordinary real estate information.

Means for Solving the Problems

[0005] This invention provides a means for analyzing an individual's lifestyle and living environment characteristics using image data, audio data, and text data, and proposes a system that automatically selects and suggests the most suitable relocation destination based on this analysis. The system first receives user data through an input means and converts audio data into text data. Next, it analyzes the image data and the converted text data to extract the user's lifestyle and desired living environment. This allows the system to select a relocation destination that suits the user's needs and then present that information to the user. Furthermore, by receiving user feedback, re-evaluating the conditions, and generating new relocation destination candidates, the system can provide more appropriate suggestions. This can mitigate the problem of urban concentration and promote migration to rural areas.

[0006] "Means of receiving data" refers to the processes and interfaces used to collect image data, audio data, and text data entered by the user and to import them into the system.

[0007] "Means of conversion" refers to the technologies and algorithms used to convert input audio data into analyzable text data.

[0008] "Means of analysis" refers to data processing techniques used to extract characteristics of living environments and lifestyles from image data and text data.

[0009] "Selection methods" refer to the criteria and algorithms used to identify and select migration destinations that meet the user's needs, based on the analysis results.

[0010] "Means of presentation" refers to methods and interfaces for clearly communicating information about the selected relocation destination to the user.

[0011] "Means of receiving feedback" refers to the process or function of receiving evaluations and opinions from users and incorporating them into the system.

[0012] "Methods for re-evaluating conditions and generating new potential relocation destinations" refers to technologies that reconfirm user conditions based on feedback and then propose new relocation destinations based on these conditions.

[0013] "Means of transmission" refers to communication technologies and protocols used to securely send collected or generated data to the intended recipient. [Brief explanation of the drawing]

[0014] [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.

Modes for Carrying Out the Invention

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system that promotes migration to rural areas to solve the problem of over-concentration in urban areas, and it uses image data, voice data, and text data to suggest the most suitable relocation destination for an individual. The system's program processing is described below in natural language.

[0036] First, users input photos of their home and surrounding area into their device and record voice data about their desired future living environment for themselves and their family. They also input information about their current lifestyle and consumption trends in text format. This data is collected and integrated by the user's device.

[0037] The terminal sends the aggregated data to the server. The server converts the voice data into text data and analyzes all the data. Specifically, the server uses image data to evaluate the characteristics of the residence and extracts the user's lifestyle and living environment preferences from the voice and text data.

[0038] Based on the results, the server searches a nationwide database of local areas and generates potential relocation destinations that match the user's needs. The server then sends additional information, such as cost of living, convenience, and regional characteristics, to the terminal.

[0039] The terminal presents information received from the server to the user, displaying it interactively in an easy-to-understand format. The user can review this information and provide feedback. The server receives feedback from the user, re-evaluates the conditions, and can then suggest new candidate locations.

[0040] For example, if a user lives in an urban area and prioritizes raising children in a nature-rich environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential rural locations. Furthermore, it will provide detailed information on housing costs and living infrastructure in those areas, helping the user consider a concrete relocation plan. Through this process, users can find a relocation destination that is optimized for their wishes and needs.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users take photos of their home and surrounding area and save them to their device using their smartphone or camera. They also record voice data based on their and their family's wishes and input information about their current lifestyle and consumption trends in text format.

[0044] Step 2:

[0045] The terminal integrates the image, audio, and text data entered by the user into a single dataset and prepares it for transmission to the server. The data undergoes preprocessing, such as format conversion.

[0046] Step 3:

[0047] The terminal sends the prepared data to the server and simultaneously notifies the user of the transmission progress. After the transmission is complete, the user is shown a message prompting them to proceed to the next step.

[0048] Step 4:

[0049] The server receives data sent from the terminal and performs a speech recognition process to convert the audio data into text data. It then integrates the results with other data.

[0050] Step 5:

[0051] The server analyzes the integrated dataset and extracts features of the living environment (e.g., house size, room layout) from the image data. Similarly, it uses the converted text data to identify the user's lifestyle and desired living environment requirements.

[0052] Step 6:

[0053] Based on the analysis results, the server references a nationwide database of local areas and selects multiple potential relocation destinations that match the user's needs. It also searches for detailed information related to each candidate (such as cost of living, transportation access, and regional characteristics).

[0054] Step 7:

[0055] The server sends the selected migration destination candidates and their detailed information to the terminal. This prepares the terminal to present this information to the user.

[0056] Step 8:

[0057] The device visually presents the received information on potential relocation destinations to the user in an interactive format. The user can review this information and view detailed content related to selecting a relocation destination.

[0058] Step 9:

[0059] The user enters feedback about the presented candidate locations into the device. This feedback may include requests for further adjustments to the conditions or requests for alternative options.

[0060] Step 10:

[0061] The server receives feedback from the user and initiates a re-evaluation process of the conditions. If necessary, it generates and re-proposes new migration destinations.

[0062] (Example 1)

[0063] 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."

[0064] The challenge lies in providing an effective support system to alleviate urban overcrowding and promote optimal rural migration for individuals. In particular, there is a need to be able to quickly and accurately propose suitable relocation destinations based on individual lifestyles and preferences.

[0065] 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.

[0066] In this invention, the server includes means for receiving diverse data input by an individual, means for performing data analysis using technology to convert voice data into text data, and means for evaluating the characteristics of image data and text data to extract features of the living environment and lifestyle. This makes it possible to easily determine the optimal relocation destination based on the user's requests.

[0067] "Diverse data" refers to data that includes information in different formats, such as image data, audio data, and text data.

[0068] "Technology for converting audio data into text data" refers to automatic speech recognition technology that converts speech into text information, thereby making audio input into a text format that can be analyzed.

[0069] "Characteristics of the living environment and lifestyle" refers to characteristics related to the place of residence and lifestyle, and includes the structure of the dwelling, the surrounding environment, and lifestyle habits.

[0070] "A relocation destination that meets the user's needs" refers to a new place of residence selected in light of the user's specific needs and desires.

[0071] "Providing information visually" means displaying information to users in an easy-to-understand manner using images and graphics.

[0072] "Receiving responses, re-evaluating requirements, and generating new relocation options" refers to the process of reviewing conditions based on feedback provided by users and proposing new potential relocation destinations.

[0073] "Integrating data in different formats" refers to the process of unifying data expressed in multiple formats and combining them into a form that can be used effectively.

[0074] "Maintaining the security of information and transmitting it to the processing device" means transmitting data to the processing device while maintaining the confidentiality and integrity of the data.

[0075] This invention relates to a system that suggests the optimal relocation destination based on an individual's lifestyle and desired living environment. This system includes terminals, servers, and communication means connecting them.

[0076] Users take photos of their homes using their devices, inputting visual data of the interior and surrounding environment. Simultaneously, they record audio data to provide information about their desired living environment and lifestyle. They can also input detailed information about their current habits and consumption trends as text data. This data is integrated on the device and transmitted to the server using a secure protocol.

[0077] The server processes data using various conversion and analysis techniques. Specifically, it uses automatic speech recognition (ASR) technology to convert speech data into text data. This technology can utilize voice services from common cloud infrastructures. The server also analyzes visual data using image analysis technology to evaluate living characteristics. Furthermore, it uses natural language processing (NLP) technology to analyze text data and extract the user's lifestyle and preferences. Widely used AI libraries and APIs can be utilized for these technologies.

[0078] The server uses a generative AI model, based on features extracted from the user, to search a nationwide regional database and generate optimal relocation destinations. This candidate location data includes factors such as cost of living, convenience, and regional characteristics. The generated information is then sent back to the terminal.

[0079] The terminal interactively presents the user with potential relocation destinations received from the server. This display is presented visually in map or list format, allowing the user to view and select detailed information. User feedback is sent back to the server and used to re-evaluate the conditions and generate new potential locations.

[0080] For example, if a user lives in an urban area and desires to raise their children in a rich natural environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential options. This allows the user to compare and consider detailed housing costs and living infrastructure information, and then formulate a concrete relocation plan.

[0081] An example of a prompt message is: "Create a system that suggests the optimal relocation destination based on the user's desired living environment and lifestyle. Specific conditions should include a rich natural environment, excellent educational facilities, and low cost of living."

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] Users take photos of their home and surroundings using a device and input them as digital data. They also record information about their desired living environment and lifestyle using voice input, generating audio data that can be converted into text. Furthermore, they input their daily habits and consumption trends as text. As a result, image data, audio data, and text data are aggregated on the device.

[0085] Step 2:

[0086] The device sends the aggregated data to the server using the SSL / TLS protocol. The data sent includes images, audio, and text that detail the user's preferences. Data confidentiality and integrity are maintained throughout this process. After transmission, the device notifies the user of the completion of the transmission.

[0087] Step 3:

[0088] The server converts the received audio data into text data using automatic speech recognition (ASR) technology. Specifically, it analyzes the audio waveform using a speech recognition API and outputs the corresponding text. As a result, the information obtained from the audio is stored on the server as text data.

[0089] Step 4:

[0090] The server analyzes the received image data using image analysis technology to evaluate the characteristics of the living space. This involves using AI models to recognize objects and scenes within the image. This process yields feature information extracted from the image.

[0091] Step 5:

[0092] The server analyzes the converted audio and text data using natural language processing (NLP) techniques to extract the user's lifestyle and living environment preferences. The NLP model understands key keywords and context from the input data and converts them into quantifiable data.

[0093] Step 6:

[0094] Based on the analysis results, the server uses a generative AI model to search a nationwide regional database and generate potential relocation destinations that match the user's requirements. The generative AI model matches the user's desired characteristics with the characteristics of the region to select the most suitable candidate location. As a result, a list of highly suitable relocation destinations is generated on the server.

[0095] Step 7:

[0096] The server collects additional information, including cost of living, convenience, and local characteristics, and sends it to the user's terminal along with a curated list of potential relocation destinations. This information is presented in a format that is intuitively understandable to the user.

[0097] Step 8:

[0098] The terminal presents the user with candidate location information received from the server. This information is displayed in interactive map or list formats, allowing the user to examine details. This enables the user to compare and select from various candidate locations.

[0099] Step 9:

[0100] The user reviews the information on the presented candidate locations and provides feedback. This feedback may include reasons for selection and changes to the criteria. The device sends the feedback to the server, and the user's opinions are incorporated.

[0101] Step 10:

[0102] The server re-evaluates the conditions using user feedback and generates new potential relocation destinations as needed. The re-evaluation process is carried out to enable the presentation of more accurate candidate locations and to provide the optimal plan according to the user's needs.

[0103] (Application Example 1)

[0104] 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."

[0105] There is a challenge in mitigating the problem of over-concentration in urban areas by promoting migration to rural areas by providing individuals considering relocation with specific information about living environments. However, simply presenting data is not effective support, as users cannot fully understand the appeal of their relocation destination or imagine what life would actually be like there. Furthermore, there is a need to further improve the accuracy of selecting relocation destinations that are suitable for the user's needs.

[0106] 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.

[0107] In this invention, the server includes means for receiving visual data, auditory data, and text data input by an individual; means for converting auditory data into text data; means for analyzing the visual data and text data to extract characteristics of living conditions and lifestyles; means for selecting potential relocation sites that suit the user's needs; means for presenting information on the selected relocation sites to the user; and means for controlling a visual device for providing a virtual experience of the selected relocation sites. This makes it possible for the user to form a more concrete image of their relocation destination and simulate actual life there.

[0108] "Visual data" refers to data, including images and videos, provided by individuals, and serves as a source of information for understanding living conditions and characteristics of the living environment.

[0109] "Auditory data" refers to data provided by individuals in audio format, which can serve as clues to extract information about users' lifestyles and housing preferences.

[0110] "Text data" refers to data entered by users as text, and includes detailed information about lifestyle patterns and consumption trends.

[0111] A "visual device" is a hardware device that provides users with a virtual reality experience and helps them understand the selected potential relocation sites more concretely.

[0112] The system based on this invention has the function of suggesting the most suitable relocation destination to the user using visual, auditory, and textual data provided by the individual. The system is configured as follows:

[0113] The server receives visual data from the user's device. This visual data consists of images and videos containing information to understand the living environment and living conditions. Simultaneously, the device also receives auditory data provided as audio, which the server converts into text data. This auditory data is used to understand the user's lifestyle and preferences regarding their place of residence.

[0114] The server then analyzes the aggregated visual and textual data, employing methods to extract characteristics of living conditions and lifestyles. This analysis utilizes generative AI models to effectively identify patterns in the data.

[0115] Based on the analysis results, the server selects potential relocation sites that meet the user's needs. Information about the selected sites is presented to the user via a terminal. Furthermore, it controls a program that provides a virtual reality experience through visual devices, allowing the user to virtually experience the candidate sites. These visual devices include smart glasses and head-mounted displays.

[0116] This allows users to gain a more concrete understanding of their chosen relocation destination and visualize what it would be like to actually live there. Specifically, for example, users can experience the beautiful scenery, shopping streets, and diverse facilities of the region through virtual tours.

[0117] When giving instructions to the generative AI model, a prompt such as "Create a 360-degree panoramic video and audio guide for visiting a shopping street in Nagano Prefecture" is used. This enhances the quality of the user experience and supports the selection of the optimal relocation destination.

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

[0119] Step 1:

[0120] Users input visual data, such as photos of their home and its surroundings, into the device. They also record audio data, such as voice recordings of their and their family's desired future living environment. Furthermore, they input text data, such as information about their current lifestyle and consumption trends. All of this data is aggregated on the device.

[0121] Step 2:

[0122] The terminal sends aggregated visual, auditory, and text data to the server. The server uses speech recognition technology to convert the received auditory data into text data. This conversion allows the user's lifestyle and housing requirements to be expressed in written form.

[0123] Step 3:

[0124] The server analyzes the converted text and visual data and uses a generative AI model to extract characteristics of living conditions and lifestyles. This analysis process considers parameters such as population density, green space area, and living infrastructure. The output is a set of characteristics designed to meet user needs.

[0125] Step 4:

[0126] Based on the analysis results, the server selects the most suitable relocation destination for the user's needs. The selection process utilizes a nationwide database of local areas, specifically considering factors such as cost of living, environmental resources, and regional cultural characteristics.

[0127] Step 5:

[0128] The server presents information about the selected relocation sites to the user using visual devices. Through a terminal connected to smart glasses or a head-mounted display, the user can virtually experience the selected region. At this stage, 360-degree panoramic video and audio guidance are provided.

[0129] Step 6:

[0130] After a customized virtual experience, users provide opinions and feedback on the selected region via their device. The server receives this feedback, re-evaluates the criteria, and proposes new potential relocation sites, thereby providing more accurate recommendations.

[0131] 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.

[0132] This invention is a system that highly personalizes the individual's relocation destination selection process by combining an emotion engine that recognizes the user's emotions. In addition to conventional data analysis, this system takes into account the user's emotional state, making it possible to suggest more appropriate and satisfying relocation destinations.

[0133] First, the user takes photos of their home and its surroundings using the device, and inputs information about their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device utilizes an emotion engine to recognize the user's emotional state from the audio and image data.

[0134] The device sends the collected data to the server as a single dataset. The server converts the audio data into text and analyzes the image data to extract characteristics of the living environment. Meanwhile, the user's emotional state (e.g., joy, surprise, anxiety) analyzed by the emotion engine is also evaluated and linked to the individual data.

[0135] Based on the sentiment analysis results, the server selects the most suitable relocation destination from a nationwide regional database that best matches the user's needs and emotions. The selection criteria incorporate prioritization based on the user's emotions, aiming not only for lifestyle fit but also for the user's emotional fulfillment.

[0136] Information on the selected relocation destination, including detailed cost of living, transportation access, and local characteristics, is transmitted to the device. The device then presents this information to the user in an interactive format to encourage consideration.

[0137] For example, if a user desires a quieter environment to reduce stress, and this information is recognized as "anxiety" by the emotion engine, the server will prioritize suggesting rural areas that are considered relatively quiet. This allows the user to make a choice that is emotionally satisfying.

[0138] Subsequently, user feedback is analyzed by the emotion engine and used to create new suggestions. Specifically, the conditions can be re-evaluated based on the user's reaction to the suggested relocation destinations, and the selection criteria can be modified as needed. This ensures that suggestions that consistently meet the user's emotional needs can be provided.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] Users take photos of their home and surrounding area using smartphones or tablets and input them into the system. They also record voice data of family opinions and their own wishes on their devices, and input information about their lifestyle and consumption patterns as text.

[0142] Step 2:

[0143] The device analyzes the input image and audio data and uses an emotion engine to recognize the user's emotional state. For example, it determines emotions such as "joy," "anxiety," and "surprise" from the tone of voice and facial expressions.

[0144] Step 3:

[0145] The terminal integrates to send collected image data, audio data, text data, and analyzed sentiment data to a server. This data is converted to an appropriate format and transmitted over a secure communication channel.

[0146] Step 4:

[0147] The server receives data sent from the terminal and applies natural language processing to convert the audio data into text data. In this process, keywords and phrases extracted from the audio are also analyzed.

[0148] Step 5:

[0149] The server uses image data to analyze the characteristics of residences and living environments. For example, it extracts elements such as interior style, house size, and brightness from photographs. At the same time, it considers emotional data to identify lifestyle tendencies and desired living environments based on that data.

[0150] Step 6:

[0151] The server combines user needs and emotional data to search for the most suitable relocation destination from a nationwide regional database. In the selection process, factors such as cost of living, transportation convenience, and regional characteristics are considered, as well as elements that contribute to the user's emotional well-being.

[0152] Step 7:

[0153] The server sends the selected relocation candidates to the user's terminal along with detailed information. This information includes photos of the area, cost of living, access information, and the availability of facilities, supporting the user's relocation decision-making.

[0154] Step 8:

[0155] The terminal displays information about potential relocation destinations received from the server to the user. The display is interactive, allowing the user to compare the advantages and disadvantages of each candidate location in detail.

[0156] Step 9:

[0157] Based on the information provided, users input feedback about each candidate location into their device. This feedback may include requests for more detailed information or suggestions to readjust the selection criteria.

[0158] Step 10:

[0159] The server receives feedback from the user and re-analyzes it using an emotion engine to evaluate the emotional state during the feedback process. Based on these results, it re-evaluates the conditions and generates and re-proposes new migration destination candidates.

[0160] (Example 2)

[0161] 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".

[0162] In modern society, selecting a relocation destination based on an individual's lifestyle and emotions is complex, and traditional data analysis methods struggle to provide recommendations that take emotional satisfaction into account. Furthermore, there is a need to process diverse user data formats quickly and securely.

[0163] 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.

[0164] In this invention, the server includes means for receiving image data, audio data, and text data from an individual's terminal; means for evaluating the user's emotional state using an emotion analysis engine and linking it to individual data; and means for integrating multiple data formats, generating a dataset including the emotion analysis results, and transmitting it securely. This enables personalized relocation suggestions that take into account the user's emotional satisfaction.

[0165] A "terminal" is a device operated by a user and is used to collect, input, and display information.

[0166] "Image data" refers to data that represents visual information in a digital format and is acquired using devices such as cameras.

[0167] "Audio data" refers to data that records the user's voice or sound as a digital signal and converts it into a format that can be processed.

[0168] "Text data" refers to data that represents character information in a digital format and is generated through user input.

[0169] A "sentiment analysis engine" is a software module that automatically analyzes a user's emotional state using nonverbal cues extracted from voice and image data.

[0170] A "dataset" is a collection of data that integrates various types of collected and processed data, and is used for analysis and transmission.

[0171] "Security" refers to the technologies and measures used to protect the confidentiality, integrity, and availability of data, and to prevent unauthorized access and data breaches.

[0172] "Destination" refers to the region or housing options that the user is considering for their new residence.

[0173] This invention relates to a system that suggests suitable relocation destinations based on a user's emotions and lifestyle. This system is implemented using a combination of hardware and software, including a terminal, an emotion analysis engine, image recognition technology, a natural language processing module, and security measures.

[0174] The user uses the device to photograph their home and surrounding environment, and inputs their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device uses an emotion analysis engine to analyze the user's emotional state from the audio and image data. The emotion analysis engine evaluates nonverbal cues such as the user's utterances, tone of voice, and facial expressions, and identifies the user's emotional state as "joy," "surprise," or "anxiety."

[0175] The collected data is transmitted to the server via a secure protocol. The server uses a natural language processing module to convert the audio data into text and image recognition technology to analyze the characteristics of the living environment. Emotional states are also linked to this data.

[0176] The server integrates sentiment analysis results and lifestyle information, and uses a relocation destination selection algorithm to select a suitable relocation destination from a nationwide database based on the user's preferences. The selection process takes into account user emotional priorities, and suggestions are made to enhance user satisfaction.

[0177] Information on the selected relocation destination, including detailed living costs, transportation access, and local characteristics, is transmitted to the device and presented to the user in an interactive format.

[0178] For example, if a user wants to reduce stress and this emotional state is recognized as "anxiety," the server will prioritize suggesting quiet, rural areas. This process allows the user to make emotionally satisfying choices.

[0179] (Example of a prompt message)

[0180] "If a user desires a quiet environment, but this is perceived as a feeling of anxiety, what kind of relocation destination would be appropriate?"

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] Users use their devices to photograph their homes and surrounding environments and input information about their lifestyles and consumption trends in text format. Image and text data are collected using the device's camera and keyboard or touchscreen. Furthermore, they record their family's opinions and their own thoughts as audio data. Thus, the input data includes images, text, and audio.

[0184] Step 2:

[0185] The terminal converts the collected audio data into text data using a natural language processing module. This process involves analyzing the audio signal, extracting linguistic features, and converting them into corresponding text. The output is the audio data converted into text format.

[0186] Step 3:

[0187] The device uses an emotion analysis engine to analyze audio and image data and evaluate the user's emotional state. This analysis process extracts nonverbal cues from the tone of voice and facial expressions in the images, classifying emotions into categories such as "joy," "surprise," and "anxiety." The output is the analyzed emotional state.

[0188] Step 4:

[0189] The terminal integrates the collected and analyzed data into a single dataset and sends it to the server via a secure protocol. At this stage, the input images, text, and analysis results are securely packaged and sent out. The integrated dataset arrives at the server as output.

[0190] Step 5:

[0191] The server uses image recognition technology to extract characteristics of the living environment based on the incoming dataset. Simultaneously, it combines sentiment analysis results with text information to select a relocation destination suitable for the user's lifestyle and emotions. The selection process includes analyzing multidimensional data correlations to identify the most matching region. The output is the selected relocation destination.

[0192] Step 6:

[0193] The server sends detailed information about the selected relocation destination to the terminal. This information includes cost of living, transportation access, and local characteristics, enabling the user to make an informed decision. This output interactively provides the user with the information they want to know.

[0194] Step 7:

[0195] The user provides feedback on the presented relocation information. The device then analyzes this feedback again using a sentiment analysis engine and sends the results to the server. Further user desires and dissatisfactions are collected from the feedback input as text or audio data.

[0196] Step 8:

[0197] The server uses the collected feedback to re-evaluate existing data assessments and, if necessary, generate new migration destination suggestions. Here, the sentiment factors obtained from the feedback are incorporated as a new dataset and the re-evaluation process is performed. As output, improved migration destination suggestions are provided.

[0198] (Application Example 2)

[0199] 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".

[0200] In modern commercial facilities and sales environments, accurately understanding customer emotions and needs and making appropriate suggestions on the spot presents a challenge. In such situations, the customer experience may not be optimized, potentially leading to lost sales opportunities. Therefore, there is a need to sense customer reactions in real time and provide personalized product suggestions accordingly.

[0201] 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.

[0202] In this invention, the server includes means for receiving image data, voice data, and text data input by an individual; means for converting voice information into text information; means for analyzing the image data and text data to extract characteristics of the living environment and lifestyle; means for recognizing the user's emotional state and selecting candidates that match the user's emotions and needs; means for suggesting products based on the user's emotional analysis; and means for presenting the selected product or regional information to the user. This enables accurate product suggestions based on the customer's emotional state, improving the sales experience and reducing lost opportunities.

[0203] "Image data" refers to digital data that includes visual information entered by an individual.

[0204] "Audio data" refers to information recorded as digital signals of sounds emitted by an individual.

[0205] "Text data" refers to digital information in the form of written characters or sentences.

[0206] "Means of converting audio information into text information" refers to processing devices or software used to convert audio data into text data.

[0207] "Means for extracting characteristics of living environments and lifestyles" refers to technologies that analyze living environments and behavioral patterns from input data to identify their characteristics.

[0208] "Recognizing the user's emotional state" is the process of determining the type and intensity of emotions from the user's input data.

[0209] "Means of selecting candidates" refers to the process of presenting options that match the user's emotions and needs.

[0210] "Means of proposing products" refers to methods for presenting products suitable for customers based on analyzed data.

[0211] "Means of presenting information to the user" refers to devices or systems that inform the user of selected information visually or audibly.

[0212] This invention can be implemented as a customer suggestion system in a sales environment utilizing smart glasses. The server receives image data, audio data, and text data collected by the smart glasses. Smart glasses may include devices such as Google® Glass®. Audio data is converted into text data using on-device emotion recognition software and sent to a cloud service such as Microsoft® Azure® Cognition Services.

[0213] The server utilizes image and text data to analyze the customer's living environment and lifestyle, extracting its characteristics. Furthermore, it identifies the customer's emotional state through an emotion engine and selects product candidates that are suitable for the customer's needs based on this information.

[0214] The selected product information is displayed on the smart glasses' screen, and the salesperson can suggest or explain it to the customer. For example, if the customer's facial expression indicates anxiety, the system can suggest an aromatherapy candle as a stress-relieving product.

[0215] The user's reaction to this suggestion is also analyzed by the emotion engine and sent to the server. Based on the user's feedback, the server optimizes the suggestion and generates new product candidates.

[0216] An example of a specific prompt for a generative AI model is: "I would like advice on which products in the store to recommend when a customer appears anxious." By using this prompt, the system can instantly respond to diverse customer needs and realize a highly personalized sales strategy.

[0217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0218] Step 1:

[0219] The device collects image and audio data from the customer through smart glasses. This records the customer's facial expressions and the moment they speak. The input is image and audio, and the raw data is stored in the device as output.

[0220] Step 2:

[0221] The device performs the process of converting audio data into text data. Using speech recognition software, it analyzes the recorded audio data and converts it into text. This allows the content of the audio to be obtained as text information.

[0222] Step 3:

[0223] The server analyzes the received image and text data. Using AI image analysis technology, emotions are extracted from the customer's facial expressions and movements. The text data is understood through natural language processing. The output of this step is information about the customer's emotional state and lifestyle.

[0224] Step 4:

[0225] The server performs preprocessing, and the emotion engine analyzes the emotional state in detail. A generative AI model is used to quantify the user's emotions and optimize candidate products. The input is analyzed data, and the output is a recommendation algorithm based on the emotional state.

[0226] Step 5:

[0227] The server generates product suggestions tailored to the user's emotions and needs based on the analysis results and sends them to the terminal. The products presented are aligned with the customer's emotional state, aiming to provide an optimal purchasing experience.

[0228] Step 6:

[0229] Users interactively receive results and make selections and provide feedback on the displayed products. They view product information on the smart glasses display, and their responses are recorded based on their satisfaction level.

[0230] Step 7:

[0231] The device sends the user's response back to the server. This feedback is necessary for generating new suggestions and, after sentiment analysis, becomes input for the next step. The server continuously improves the system based on the collected feedback.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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".

[0248] This invention is a system that promotes migration to rural areas to solve the problem of over-concentration in urban areas, and it uses image data, audio data, and text data to suggest the most suitable relocation destination for an individual. The processing of the system's program is described below in natural language.

[0249] First, users input photos of their home and surrounding area into their device and record voice data about their desired future living environment for themselves and their family. They also input information about their current lifestyle and consumption trends in text format. This data is collected and integrated by the user's device.

[0250] The terminal sends the aggregated data to the server. The server converts the voice data into text data and analyzes all the data. Specifically, the server uses image data to evaluate the characteristics of the residence and extracts the user's lifestyle and living environment preferences from the voice and text data.

[0251] Based on the results, the server searches a nationwide database of local areas and generates potential relocation destinations that match the user's needs. The server then sends additional information, such as cost of living, convenience, and regional characteristics, to the terminal.

[0252] The terminal presents information received from the server to the user, displaying it interactively in an easy-to-understand format. The user can review this information and provide feedback. The server receives feedback from the user, re-evaluates the conditions, and can then suggest new candidate locations.

[0253] For example, if a user lives in an urban area and prioritizes raising children in a nature-rich environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential rural locations. Furthermore, it will provide detailed information on housing costs and living infrastructure in those areas, helping the user consider a concrete relocation plan. Through this process, users can find a relocation destination that is optimized for their wishes and needs.

[0254] The following describes the processing flow.

[0255] Step 1:

[0256] Users take photos of their home and surrounding area and save them to their device using their smartphone or camera. They also record voice data based on their and their family's wishes and input information about their current lifestyle and consumption trends in text format.

[0257] Step 2:

[0258] The terminal integrates the image, audio, and text data entered by the user into a single dataset and prepares it for transmission to the server. The data undergoes preprocessing, such as format conversion.

[0259] Step 3:

[0260] The terminal sends the prepared data to the server and simultaneously notifies the user of the transmission progress. After the transmission is complete, the user is shown a message prompting them to proceed to the next step.

[0261] Step 4:

[0262] The server receives data sent from the terminal and performs a speech recognition process to convert the audio data into text data. It then integrates the results with other data.

[0263] Step 5:

[0264] The server analyzes the integrated dataset and extracts features of the living environment (e.g., house size, room layout) from the image data. Similarly, it uses the converted text data to identify the user's lifestyle and desired living environment requirements.

[0265] Step 6:

[0266] Based on the analysis results, the server references a nationwide database of local areas and selects multiple potential relocation destinations that match the user's needs. It also searches for detailed information related to each candidate (such as cost of living, transportation access, and regional characteristics).

[0267] Step 7:

[0268] The server sends the selected migration destination candidates and their detailed information to the terminal. This prepares the terminal to present this information to the user.

[0269] Step 8:

[0270] The device visually presents the received information on potential relocation destinations to the user in an interactive format. The user can review this information and view detailed content related to selecting a relocation destination.

[0271] Step 9:

[0272] The user enters feedback about the presented candidate locations into the device. This feedback may include requests for further adjustments to the conditions or requests for alternative options.

[0273] Step 10:

[0274] The server receives feedback from the user and initiates a re-evaluation process of the conditions. If necessary, it generates and re-proposes new migration destinations.

[0275] (Example 1)

[0276] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0277] The challenge lies in providing an effective support system to alleviate urban overcrowding and promote optimal rural migration for individuals. In particular, there is a need to be able to quickly and accurately propose suitable relocation destinations based on individual lifestyles and preferences.

[0278] 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.

[0279] In this invention, the server includes means for receiving various data input by an individual, means for performing data analysis using a technique for converting voice data into text data, and means for evaluating the characteristics of image data and text data and extracting characteristics of the living environment and lifestyle. This makes it possible to easily determine an optimal relocation destination candidate based on the user's desires.

[0280] "Various data" refers to data including information in different formats such as image data, voice data, and text data.

[0281] "The technique for converting voice data into text data" refers to the automatic speech recognition technique for converting voice into character information, thereby converting voice input into a text format that can be analyzed.

[0282] "Characteristics of the living environment and lifestyle" refer to characteristics related to the place of residence and lifestyle, including the structure of the dwelling, the surrounding environment, living habits, etc.

[0283] "A relocation destination that meets the user's needs" refers to a new place of residence selected in light of the user's specific needs and wishes.

[0284] "Visually provide" means to clearly display information to the user using images and graphics.

[0285] "Receive a response, re-evaluate the requirements, and generate a new relocation destination plan" refers to the process of reexamining the conditions based on the feedback provided by the user and proposing a new relocation candidate area.

[0286] "Integrate different forms of data" is an operation of unifying data expressed in multiple forms and summarizing it into an effectively usable form.

[0287] "Maintain the security of information and transmit it to the processing device" means transmitting data to the device for processing while maintaining the confidentiality and integrity of the data.

[0288] This invention relates to a system that suggests the optimal relocation destination based on an individual's lifestyle and desired living environment. This system includes terminals, servers, and communication means connecting them.

[0289] Users take photos of their homes using their devices, inputting visual data of the interior and surrounding environment. Simultaneously, they record audio data to provide information about their desired living environment and lifestyle. They can also input detailed information about their current habits and consumption trends as text data. This data is integrated on the device and transmitted to the server using a secure protocol.

[0290] The server processes data using various conversion and analysis techniques. Specifically, it uses automatic speech recognition (ASR) technology to convert speech data into text data. This technology can utilize voice services from common cloud infrastructures. The server also analyzes visual data using image analysis technology to evaluate living characteristics. Furthermore, it uses natural language processing (NLP) technology to analyze text data and extract the user's lifestyle and preferences. Widely used AI libraries and APIs can be utilized for these technologies.

[0291] The server uses a generative AI model, based on features extracted from the user, to search a nationwide regional database and generate optimal relocation destinations. This candidate location data includes factors such as cost of living, convenience, and regional characteristics. The generated information is then sent back to the terminal.

[0292] The terminal interactively presents the user with potential relocation destinations received from the server. This display is presented visually in map or list format, allowing the user to view and select detailed information. User feedback is sent back to the server and used to re-evaluate the conditions and generate new potential locations.

[0293] For example, if a user lives in an urban area and desires to raise their children in a rich natural environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential options. This allows the user to compare and consider detailed housing costs and living infrastructure information, and then formulate a concrete relocation plan.

[0294] An example of a prompt message is: "Create a system that suggests the optimal relocation destination based on the user's desired living environment and lifestyle. Specific conditions should include a rich natural environment, excellent educational facilities, and low cost of living."

[0295] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0296] Step 1:

[0297] Users take photos of their home and surroundings using a device and input them as digital data. They also record information about their desired living environment and lifestyle using voice input, generating audio data that can be converted into text. Furthermore, they input their daily habits and consumption trends as text. As a result, image data, audio data, and text data are aggregated on the device.

[0298] Step 2:

[0299] The device sends the aggregated data to the server using the SSL / TLS protocol. The data sent includes images, audio, and text that detail the user's preferences. Data confidentiality and integrity are maintained throughout this process. After transmission, the device notifies the user of the completion of the transmission.

[0300] Step 3:

[0301] The server converts the received voice data into text data using automatic speech recognition (ASR) technology. Specifically, it analyzes the voice waveform using a speech recognition API and outputs the corresponding text. As a result, the information obtained from the voice is retained in the server as text data.

[0302] Step 4:

[0303] The server analyzes the received image data using image analysis technology to evaluate the living characteristics. For this, an AI model for recognizing objects and scenes in the image is used. Through this process, feature information extracted from the image is obtained.

[0304] Step 5:

[0305] The server analyzes the converted voice data and text data using natural language processing (NLP) technology to extract the user's lifestyle and living environment preferences. The NLP model understands important keywords and context from the input data and converts them into quantified data.

[0306] Step 6:

[0307] The server uses a generative AI model based on the analysis results to search the national local database and generate migration destination candidates that meet the user's requirements. The generative AI model matches the user's desired characteristics with the characteristics of the region to select the optimal candidate location. As a result, a list of highly suitable migration candidate locations is generated within the server.

[0308] Step 7:

[0309] The server collects additional information including living costs, convenience, and regional characteristics, and transmits it to the terminal together with the organized migration destination candidates. This information is created in a format that the user can intuitively understand.

[0310] Step 8:

[0311] The terminal presents the user with candidate location information received from the server. This information is displayed in interactive map or list formats, allowing the user to examine details. This enables the user to compare and select from various candidate locations.

[0312] Step 9:

[0313] The user reviews the information on the presented candidate locations and provides feedback. This feedback may include reasons for selection and changes to the criteria. The device sends the feedback to the server, and the user's opinions are incorporated.

[0314] Step 10:

[0315] The server re-evaluates the conditions using user feedback and generates new potential relocation destinations as needed. The re-evaluation process is carried out to enable the presentation of more accurate candidate locations and to provide the optimal plan according to the user's needs.

[0316] (Application Example 1)

[0317] 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."

[0318] There is a challenge in mitigating the problem of over-concentration in urban areas by promoting migration to rural areas by providing individuals considering relocation with specific information about living environments. However, simply presenting data is not effective support, as users cannot fully understand the appeal of their relocation destination or imagine what life would actually be like there. Furthermore, there is a need to further improve the accuracy of selecting relocation destinations that are suitable for the user's needs.

[0319] 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.

[0320] In this invention, the server includes means for receiving visual data, auditory data, and text data input by an individual; means for converting auditory data into text data; means for analyzing the visual data and text data to extract characteristics of living conditions and lifestyles; means for selecting potential relocation sites that suit the user's needs; means for presenting information on the selected relocation sites to the user; and means for controlling a visual device for providing a virtual experience of the selected relocation sites. This makes it possible for the user to form a more concrete image of their relocation destination and simulate actual life there.

[0321] "Visual data" refers to data, including images and videos, provided by individuals, and serves as a source of information for understanding living conditions and characteristics of the living environment.

[0322] "Auditory data" refers to data provided by individuals in audio format, which can serve as clues to extract information about users' lifestyles and housing preferences.

[0323] "Text data" refers to data entered by users as text, and includes detailed information about lifestyle patterns and consumption trends.

[0324] A "visual device" is a hardware device that provides users with a virtual reality experience and helps them understand the selected potential relocation sites more concretely.

[0325] The system based on this invention has the function of suggesting the most suitable relocation destination to the user using visual, auditory, and textual data provided by the individual. The system is configured as follows:

[0326] The server receives visual data from the user's device. This visual data consists of images and videos containing information to understand the living environment and living conditions. Simultaneously, the device also receives auditory data provided as audio, which the server converts into text data. This auditory data is used to understand the user's lifestyle and preferences regarding their place of residence.

[0327] The server then analyzes the aggregated visual and textual data, employing methods to extract characteristics of living conditions and lifestyles. This analysis utilizes generative AI models to effectively identify patterns in the data.

[0328] Based on the analysis results, the server selects potential relocation sites that meet the user's needs. Information about the selected sites is presented to the user via a terminal. Furthermore, it controls a program that provides a virtual reality experience through visual devices, allowing the user to virtually experience the candidate sites. These visual devices include smart glasses and head-mounted displays.

[0329] This allows users to gain a more concrete understanding of their chosen relocation destination and visualize what it would be like to actually live there. Specifically, for example, users can experience the beautiful scenery, shopping streets, and diverse facilities of the region through virtual tours.

[0330] When giving instructions to the generative AI model, a prompt such as "Create a 360-degree panoramic video and audio guide for visiting a shopping street in Nagano Prefecture" is used. This enhances the quality of the user experience and supports the selection of the optimal relocation destination.

[0331] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0332] Step 1:

[0333] Users input visual data, such as photos of their home and its surroundings, into the device. They also record audio data, such as voice recordings of their and their family's desired future living environment. Furthermore, they input text data, such as information about their current lifestyle and consumption trends. All of this data is aggregated on the device.

[0334] Step 2:

[0335] The terminal sends aggregated visual, auditory, and text data to the server. The server uses speech recognition technology to convert the received auditory data into text data. This conversion allows the user's lifestyle and housing requirements to be expressed in written form.

[0336] Step 3:

[0337] The server analyzes the converted text and visual data and uses a generative AI model to extract characteristics of living conditions and lifestyles. This analysis process considers parameters such as population density, green space area, and living infrastructure. The output is a set of characteristics designed to meet user needs.

[0338] Step 4:

[0339] Based on the analysis results, the server selects the most suitable relocation destination for the user's needs. The selection process utilizes a nationwide database of local areas, specifically considering factors such as cost of living, environmental resources, and regional cultural characteristics.

[0340] Step 5:

[0341] The server presents information about the selected relocation sites to the user using visual devices. Through a terminal connected to smart glasses or a head-mounted display, the user can virtually experience the selected region. At this stage, 360-degree panoramic video and audio guidance are provided.

[0342] Step 6:

[0343] After a customized virtual experience, users provide opinions and feedback on the selected region via their device. The server receives this feedback, re-evaluates the criteria, and proposes new potential relocation sites, thereby providing more accurate recommendations.

[0344] 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.

[0345] This invention is a system that highly personalizes the individual's relocation destination selection process by combining an emotion engine that recognizes the user's emotions. In addition to conventional data analysis, this system takes into account the user's emotional state, making it possible to suggest more appropriate and satisfying relocation destinations.

[0346] First, the user takes photos of their home and its surroundings using the device, and inputs information about their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device utilizes an emotion engine to recognize the user's emotional state from the audio and image data.

[0347] The device sends the collected data to the server as a single dataset. The server converts the audio data into text and analyzes the image data to extract characteristics of the living environment. Meanwhile, the user's emotional state (e.g., joy, surprise, anxiety) analyzed by the emotion engine is also evaluated and linked to the individual data.

[0348] Based on the sentiment analysis results, the server selects the most suitable relocation destination from a nationwide regional database that best matches the user's needs and emotions. The selection criteria incorporate prioritization based on the user's emotions, aiming not only for lifestyle fit but also for the user's emotional fulfillment.

[0349] Information on the selected relocation destination, including detailed cost of living, transportation access, and local characteristics, is transmitted to the device. The device then presents this information to the user in an interactive format to encourage consideration.

[0350] For example, if a user desires a quieter environment to reduce stress, and this information is recognized as "anxiety" by the emotion engine, the server will prioritize suggesting rural areas that are considered relatively quiet. This allows the user to make a choice that is emotionally satisfying.

[0351] Subsequently, user feedback is analyzed by the emotion engine and used to create new suggestions. Specifically, the conditions can be re-evaluated based on the user's reaction to the suggested relocation destinations, and the selection criteria can be modified as needed. This ensures that suggestions that consistently meet the user's emotional needs can be provided.

[0352] The following describes the processing flow.

[0353] Step 1:

[0354] Users take photos of their home and surrounding area using smartphones or tablets and input them into the system. They also record voice data of family opinions and their own wishes on their devices, and input information about their lifestyle and consumption patterns as text.

[0355] Step 2:

[0356] The device analyzes the input image and audio data and uses an emotion engine to recognize the user's emotional state. For example, it determines emotions such as "joy," "anxiety," and "surprise" from the tone of voice and facial expressions.

[0357] Step 3:

[0358] The terminal integrates to send collected image data, audio data, text data, and analyzed sentiment data to a server. This data is converted to an appropriate format and transmitted over a secure communication channel.

[0359] Step 4:

[0360] The server receives data sent from the terminal and applies natural language processing to convert the audio data into text data. In this process, keywords and phrases extracted from the audio are also analyzed.

[0361] Step 5:

[0362] The server uses image data to analyze the characteristics of residences and living environments. For example, it extracts elements such as interior style, house size, and brightness from photographs. At the same time, it considers emotional data to identify lifestyle tendencies and desired living environments based on that data.

[0363] Step 6:

[0364] The server combines user needs and emotional data to search for the most suitable relocation destination from a nationwide regional database. In the selection process, factors such as cost of living, transportation convenience, and regional characteristics are considered, as well as elements that contribute to the user's emotional well-being.

[0365] Step 7:

[0366] The server sends the selected relocation candidates to the user's terminal along with detailed information. This information includes photos of the area, cost of living, access information, and the availability of facilities, supporting the user's relocation decision-making.

[0367] Step 8:

[0368] The terminal displays information about potential relocation destinations received from the server to the user. The display is interactive, allowing the user to compare the advantages and disadvantages of each candidate location in detail.

[0369] Step 9:

[0370] Based on the information provided, users input feedback about each candidate location into their device. This feedback may include requests for more detailed information or suggestions to readjust the selection criteria.

[0371] Step 10:

[0372] The server receives feedback from the user and re-analyzes it using an emotion engine to evaluate the emotional state during the feedback process. Based on these results, it re-evaluates the conditions and generates and re-proposes new migration destination candidates.

[0373] (Example 2)

[0374] 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".

[0375] In modern society, selecting a relocation destination based on an individual's lifestyle and emotions is complex, and traditional data analysis methods struggle to provide recommendations that take emotional satisfaction into account. Furthermore, there is a need to process diverse user data formats quickly and securely.

[0376] 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.

[0377] In this invention, the server includes means for receiving image data, audio data, and text data from an individual's terminal; means for evaluating the user's emotional state using an emotion analysis engine and linking it to individual data; and means for integrating multiple data formats, generating a dataset including the emotion analysis results, and transmitting it securely. This enables personalized relocation suggestions that take into account the user's emotional satisfaction.

[0378] A "terminal" is a device operated by a user and is used to collect, input, and display information.

[0379] "Image data" refers to data that represents visual information in a digital format and is acquired using devices such as cameras.

[0380] "Audio data" refers to data that records the user's voice or sound as a digital signal and converts it into a format that can be processed.

[0381] "Text data" refers to data that represents character information in a digital format and is generated through user input.

[0382] A "sentiment analysis engine" is a software module that automatically analyzes a user's emotional state using nonverbal cues extracted from voice and image data.

[0383] A "dataset" is a collection of data that integrates various types of collected and processed data, and is used for analysis and transmission.

[0384] "Security" refers to the technologies and measures used to protect the confidentiality, integrity, and availability of data, and to prevent unauthorized access and data breaches.

[0385] "Destination" refers to the region or housing options that the user is considering for their new residence.

[0386] This invention relates to a system that suggests suitable relocation destinations based on a user's emotions and lifestyle. This system is implemented using a combination of hardware and software, including a terminal, an emotion analysis engine, image recognition technology, a natural language processing module, and security measures.

[0387] The user uses the device to photograph their home and surrounding environment, and inputs their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device uses an emotion analysis engine to analyze the user's emotional state from the audio and image data. The emotion analysis engine evaluates nonverbal cues such as the user's utterances, tone of voice, and facial expressions, and identifies the user's emotional state as "joy," "surprise," or "anxiety."

[0388] The collected data is transmitted to the server via a secure protocol. The server uses a natural language processing module to convert the audio data into text and image recognition technology to analyze the characteristics of the living environment. Emotional states are also linked to this data.

[0389] The server integrates sentiment analysis results and lifestyle information, and uses a relocation destination selection algorithm to select a suitable relocation destination from a nationwide database based on the user's preferences. The selection process takes into account user emotional priorities, and suggestions are made to enhance user satisfaction.

[0390] Information on the selected relocation destination, including detailed living costs, transportation access, and local characteristics, is transmitted to the device and presented to the user in an interactive format.

[0391] For example, if a user wants to reduce stress and this emotional state is recognized as "anxiety," the server will prioritize suggesting quiet, rural areas. This process allows the user to make emotionally satisfying choices.

[0392] (Example of a prompt message)

[0393] "If a user desires a quiet environment, but this is perceived as a feeling of anxiety, what kind of relocation destination would be appropriate?"

[0394] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0395] Step 1:

[0396] Users use their devices to photograph their homes and surrounding environments and input information about their lifestyles and consumption trends in text format. Image and text data are collected using the device's camera and keyboard or touchscreen. Furthermore, they record their family's opinions and their own thoughts as audio data. Thus, the input data includes images, text, and audio.

[0397] Step 2:

[0398] The terminal converts the collected audio data into text data using a natural language processing module. This process involves analyzing the audio signal, extracting linguistic features, and converting them into corresponding text. The output is the audio data converted into text format.

[0399] Step 3:

[0400] The device uses an emotion analysis engine to analyze audio and image data and evaluate the user's emotional state. This analysis process extracts nonverbal cues from the tone of voice and facial expressions in the images, classifying emotions into categories such as "joy," "surprise," and "anxiety." The output is the analyzed emotional state.

[0401] Step 4:

[0402] The terminal integrates the collected and analyzed data into a single dataset and sends it to the server via a secure protocol. At this stage, the input images, text, and analysis results are securely packaged and sent out. The integrated dataset arrives at the server as output.

[0403] Step 5:

[0404] The server uses image recognition technology to extract characteristics of the living environment based on the incoming dataset. Simultaneously, it combines sentiment analysis results with text information to select a relocation destination suitable for the user's lifestyle and emotions. The selection process includes analyzing multidimensional data correlations to identify the most matching region. The output is the selected relocation destination.

[0405] Step 6:

[0406] The server sends detailed information about the selected relocation destination to the terminal. This information includes cost of living, transportation access, and local characteristics, enabling the user to make an informed decision. This output interactively provides the user with the information they want to know.

[0407] Step 7:

[0408] The user provides feedback on the presented relocation information. The device then analyzes this feedback again using a sentiment analysis engine and sends the results to the server. Further user desires and dissatisfactions are collected from the feedback input as text or audio data.

[0409] Step 8:

[0410] The server uses the collected feedback to re-evaluate existing data assessments and, if necessary, generate new migration destination suggestions. Here, the sentiment factors obtained from the feedback are incorporated as a new dataset and the re-evaluation process is performed. As output, improved migration destination suggestions are provided.

[0411] (Application Example 2)

[0412] 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."

[0413] In modern commercial facilities and sales environments, accurately understanding customer emotions and needs and making appropriate suggestions on the spot presents a challenge. In such situations, the customer experience may not be optimized, potentially leading to lost sales opportunities. Therefore, there is a need to sense customer reactions in real time and provide personalized product suggestions accordingly.

[0414] 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.

[0415] In this invention, the server includes means for receiving image data, voice data, and text data input by an individual; means for converting voice information into text information; means for analyzing the image data and text data to extract characteristics of the living environment and lifestyle; means for recognizing the user's emotional state and selecting candidates that match the user's emotions and needs; means for suggesting products based on the user's emotional analysis; and means for presenting the selected product or regional information to the user. This enables accurate product suggestions based on the customer's emotional state, improving the sales experience and reducing lost opportunities.

[0416] "Image data" refers to digital data that includes visual information entered by an individual.

[0417] "Audio data" refers to information recorded as digital signals of sounds emitted by an individual.

[0418] "Text data" refers to digital information in the form of written characters or sentences.

[0419] "Means of converting audio information into text information" refers to processing devices or software used to convert audio data into text data.

[0420] "Means for extracting characteristics of living environments and lifestyles" refers to technologies that analyze living environments and behavioral patterns from input data to identify their characteristics.

[0421] "Recognizing the user's emotional state" is the process of determining the type and intensity of emotions from the user's input data.

[0422] "Means of selecting candidates" refers to the process of presenting options that match the user's emotions and needs.

[0423] "Means of proposing products" refers to methods for presenting products suitable for customers based on analyzed data.

[0424] "Means of presenting information to the user" refers to devices or systems that inform the user of selected information visually or audibly.

[0425] This invention can be implemented as a customer suggestion system in a sales environment utilizing smart glasses. The server receives image data, audio data, and text data collected by the smart glasses. Smart glasses may include devices such as Google Glass. Audio data is converted into text data using on-device emotion recognition software and sent to a cloud service such as Microsoft Azure Cognition Services.

[0426] The server utilizes image and text data to analyze the customer's living environment and lifestyle, extracting its characteristics. Furthermore, it identifies the customer's emotional state through an emotion engine and selects product candidates that are suitable for the customer's needs based on this information.

[0427] The selected product information is displayed on the smart glasses' screen, and the salesperson can suggest or explain it to the customer. For example, if the customer's facial expression indicates anxiety, the system can suggest an aromatherapy candle as a stress-relieving product.

[0428] The user's reaction to this suggestion is also analyzed by the emotion engine and sent to the server. Based on the user's feedback, the server optimizes the suggestion and generates new product candidates.

[0429] An example of a specific prompt for a generative AI model is: "I would like advice on which products in the store to recommend when a customer appears anxious." By using this prompt, the system can instantly respond to diverse customer needs and realize a highly personalized sales strategy.

[0430] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0431] Step 1:

[0432] The device collects image and audio data from the customer through smart glasses. This records the customer's facial expressions and the moment they speak. The input is image and audio, and the raw data is stored in the device as output.

[0433] Step 2:

[0434] The device performs the process of converting audio data into text data. Using speech recognition software, it analyzes the recorded audio data and converts it into text. This allows the content of the audio to be obtained as text information.

[0435] Step 3:

[0436] The server analyzes the received image and text data. Using AI image analysis technology, emotions are extracted from the customer's facial expressions and movements. The text data is understood through natural language processing. The output of this step is information about the customer's emotional state and lifestyle.

[0437] Step 4:

[0438] The server performs preprocessing, and the emotion engine analyzes the emotional state in detail. A generative AI model is used to quantify the user's emotions and optimize candidate products. The input is analyzed data, and the output is a recommendation algorithm based on the emotional state.

[0439] Step 5:

[0440] The server generates product suggestions tailored to the user's emotions and needs based on the analysis results and sends them to the terminal. The products presented are aligned with the customer's emotional state, aiming to provide an optimal purchasing experience.

[0441] Step 6:

[0442] Users interactively receive results and make selections and provide feedback on the displayed products. They view product information on the smart glasses display, and their responses are recorded based on their satisfaction level.

[0443] Step 7:

[0444] The device sends the user's response back to the server. This feedback is necessary for generating new suggestions and, after sentiment analysis, becomes input for the next step. The server continuously improves the system based on the collected feedback.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] [Third Embodiment]

[0449] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0450] 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.

[0451] 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).

[0452] 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.

[0453] 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.

[0454] 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).

[0455] 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.

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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".

[0461] This invention is a system that promotes migration to rural areas to solve the problem of over-concentration in urban areas, and it uses image data, voice data, and text data to suggest the most suitable relocation destination for an individual. The system's program processing is described below in natural language.

[0462] First, users input photos of their home and surrounding area into their device and record voice data about their desired future living environment for themselves and their family. They also input information about their current lifestyle and consumption trends in text format. This data is collected and integrated by the user's device.

[0463] The terminal sends the aggregated data to the server. The server converts the voice data into text data and analyzes all the data. Specifically, the server uses image data to evaluate the characteristics of the residence and extracts the user's lifestyle and living environment preferences from the voice and text data.

[0464] Based on the results, the server searches a nationwide database of local areas and generates potential relocation destinations that match the user's needs. The server then sends additional information, such as cost of living, convenience, and regional characteristics, to the terminal.

[0465] The terminal presents information received from the server to the user, displaying it interactively in an easy-to-understand format. The user can review this information and provide feedback. The server receives feedback from the user, re-evaluates the conditions, and can then suggest new candidate locations.

[0466] For example, if a user lives in an urban area and prioritizes raising children in a nature-rich environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential rural locations. Furthermore, it will provide detailed information on housing costs and living infrastructure in those areas, helping the user consider a concrete relocation plan. Through this process, users can find a relocation destination that is optimized for their wishes and needs.

[0467] The following describes the processing flow.

[0468] Step 1:

[0469] Users take photos of their home and surrounding area and save them to their device using their smartphone or camera. They also record voice data based on their and their family's wishes and input information about their current lifestyle and consumption trends in text format.

[0470] Step 2:

[0471] The terminal integrates the image, audio, and text data entered by the user into a single dataset and prepares it for transmission to the server. The data undergoes preprocessing, such as format conversion.

[0472] Step 3:

[0473] The terminal sends the prepared data to the server and simultaneously notifies the user of the transmission progress. After the transmission is complete, the user is shown a message prompting them to proceed to the next step.

[0474] Step 4:

[0475] The server receives data sent from the terminal and performs a speech recognition process to convert the audio data into text data. It then integrates the results with other data.

[0476] Step 5:

[0477] The server analyzes the integrated dataset and extracts features of the living environment (e.g., house size, room layout) from the image data. Similarly, it uses the converted text data to identify the user's lifestyle and desired living environment requirements.

[0478] Step 6:

[0479] Based on the analysis results, the server references a nationwide database of local areas and selects multiple potential relocation destinations that match the user's needs. It also searches for detailed information related to each candidate (such as cost of living, transportation access, and regional characteristics).

[0480] Step 7:

[0481] The server sends the selected migration destination candidates and their detailed information to the terminal. This prepares the terminal to present this information to the user.

[0482] Step 8:

[0483] The device visually presents the received information on potential relocation destinations to the user in an interactive format. The user can review this information and view detailed content related to selecting a relocation destination.

[0484] Step 9:

[0485] The user enters feedback about the presented candidate locations into the device. This feedback may include requests for further adjustments to the conditions or requests for alternative options.

[0486] Step 10:

[0487] The server receives feedback from the user and initiates a process of re-evaluating the conditions. If necessary, it generates and re-proposes new migration destinations.

[0488] (Example 1)

[0489] 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."

[0490] The challenge lies in providing an effective support system to alleviate urban overcrowding and promote optimal rural migration for individuals. In particular, there is a need to be able to quickly and accurately propose suitable relocation destinations based on individual lifestyles and preferences.

[0491] 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.

[0492] In this invention, the server includes means for receiving diverse data input by an individual, means for performing data analysis using technology to convert voice data into text data, and means for evaluating the characteristics of image data and text data to extract features of the living environment and lifestyle. This makes it possible to easily determine the optimal relocation destination based on the user's requests.

[0493] "Diverse data" refers to data that includes information in different formats, such as image data, audio data, and text data.

[0494] "Technology for converting audio data into text data" refers to automatic speech recognition technology that converts speech into text information, thereby making audio input into a text format that can be analyzed.

[0495] "Characteristics of the living environment and lifestyle" refers to characteristics related to the place of residence and lifestyle, and includes the structure of the dwelling, the surrounding environment, and lifestyle habits.

[0496] "A relocation destination that meets the user's needs" refers to a new place of residence selected in light of the user's specific needs and desires.

[0497] "Providing information visually" means displaying information to users in an easy-to-understand manner using images and graphics.

[0498] "Receiving responses, re-evaluating requirements, and generating new relocation options" refers to the process of reviewing conditions based on feedback provided by users and proposing new potential relocation destinations.

[0499] "Integrating data in different formats" refers to the process of unifying data expressed in multiple formats and combining them into a form that can be used effectively.

[0500] "Maintaining the security of information and transmitting it to the processing device" means transmitting data to the processing device while maintaining the confidentiality and integrity of the data.

[0501] This invention relates to a system that suggests the optimal relocation destination based on an individual's lifestyle and desired living environment. This system includes terminals, servers, and communication means connecting them.

[0502] Users take photos of their homes using their devices, inputting visual data of the interior and surrounding environment. Simultaneously, they record audio data to provide information about their desired living environment and lifestyle. They can also input detailed information about their current habits and consumption trends as text data. This data is integrated on the device and transmitted to the server using a secure protocol.

[0503] The server processes data using various conversion and analysis techniques. Specifically, it uses automatic speech recognition (ASR) technology to convert speech data into text data. This technology can utilize voice services from common cloud infrastructures. The server also analyzes visual data using image analysis technology to evaluate living characteristics. Furthermore, it uses natural language processing (NLP) technology to analyze text data and extract the user's lifestyle and preferences. Widely used AI libraries and APIs can be utilized for these technologies.

[0504] The server uses a generative AI model, based on features extracted from the user, to search a nationwide regional database and generate optimal relocation destinations. This candidate location data includes factors such as cost of living, convenience, and regional characteristics. The generated information is then sent back to the terminal.

[0505] The terminal interactively presents the user with potential relocation destinations received from the server. This display is presented visually in map or list format, allowing the user to view and select detailed information. User feedback is sent back to the server and used to re-evaluate the conditions and generate new potential locations.

[0506] For example, if a user lives in an urban area and desires to raise their children in a rich natural environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential options. This allows the user to compare and consider detailed housing costs and living infrastructure information, and then formulate a concrete relocation plan.

[0507] An example of a prompt message is: "Create a system that suggests the optimal relocation destination based on the user's desired living environment and lifestyle. Specific conditions should include a rich natural environment, excellent educational facilities, and low cost of living."

[0508] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0509] Step 1:

[0510] Users take photos of their home and surroundings using a device and input them as digital data. They also record information about their desired living environment and lifestyle using voice input, generating audio data that can be converted into text. Furthermore, they input their daily habits and consumption trends as text. As a result, image data, audio data, and text data are aggregated on the device.

[0511] Step 2:

[0512] The device sends the aggregated data to the server using the SSL / TLS protocol. The data sent includes images, audio, and text that detail the user's preferences. Data confidentiality and integrity are maintained throughout this process. After transmission, the device notifies the user of the completion of the transmission.

[0513] Step 3:

[0514] The server converts the received audio data into text data using automatic speech recognition (ASR) technology. Specifically, it analyzes the audio waveform using a speech recognition API and outputs the corresponding text. As a result, the information obtained from the audio is stored on the server as text data.

[0515] Step 4:

[0516] The server analyzes the received image data using image analysis technology to evaluate the characteristics of the living space. This involves using AI models to recognize objects and scenes within the image. This process yields feature information extracted from the image.

[0517] Step 5:

[0518] The server analyzes the converted audio and text data using natural language processing (NLP) techniques to extract the user's lifestyle and living environment preferences. The NLP model understands key keywords and context from the input data and converts them into quantifiable data.

[0519] Step 6:

[0520] Based on the analysis results, the server uses a generative AI model to search a nationwide regional database and generate potential relocation destinations that match the user's requirements. The generative AI model matches the user's desired characteristics with the characteristics of the region to select the most suitable candidate location. As a result, a list of highly suitable relocation destinations is generated on the server.

[0521] Step 7:

[0522] The server collects additional information, including cost of living, convenience, and local characteristics, and sends it to the user's terminal along with a curated list of potential relocation destinations. This information is presented in a format that is intuitively understandable to the user.

[0523] Step 8:

[0524] The terminal presents the user with candidate location information received from the server. This information is displayed in interactive map and list formats, allowing the user to examine details. This enables the user to compare and select from various candidate locations.

[0525] Step 9:

[0526] The user reviews the information on the proposed locations and provides feedback. This feedback may include reasons for selection and changes to the criteria. The device sends the feedback to the server, and the user's opinions are incorporated.

[0527] Step 10:

[0528] The server re-evaluates the conditions using user feedback and generates new potential relocation destinations as needed. This re-evaluation process is carried out to enable the presentation of more accurate candidate locations and to provide the optimal plan tailored to the user's needs.

[0529] (Application Example 1)

[0530] 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."

[0531] There is a challenge in mitigating the problem of over-concentration in urban areas by promoting migration to rural areas by providing individuals considering relocation with specific information about living environments. However, simply presenting data is not effective support, as users cannot fully understand the appeal of their relocation destination or imagine what life would actually be like there. Furthermore, there is a need to further improve the accuracy of selecting relocation destinations that are suitable for the user's needs.

[0532] 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.

[0533] In this invention, the server includes means for receiving visual data, auditory data, and text data input by an individual; means for converting auditory data into text data; means for analyzing the visual data and text data to extract characteristics of living conditions and lifestyles; means for selecting potential relocation sites that suit the user's needs; means for presenting information on the selected relocation sites to the user; and means for controlling a visual device for providing a virtual experience of the selected relocation sites. This makes it possible for the user to form a more concrete image of their relocation destination and simulate actual life there.

[0534] "Visual data" refers to data, including images and videos, provided by individuals, and serves as a source of information for understanding living conditions and characteristics of the living environment.

[0535] "Auditory data" refers to data provided by individuals in audio format, which can serve as clues to extract information about users' lifestyles and housing preferences.

[0536] "Text data" refers to data entered by users as text, and includes detailed information about lifestyle patterns and consumption trends.

[0537] A "visual device" is a hardware device that provides users with a virtual reality experience and helps them understand the selected potential relocation sites more concretely.

[0538] The system based on this invention has the function of suggesting the most suitable relocation destination to the user using visual, auditory, and textual data provided by the individual. The system is configured as follows:

[0539] The server receives visual data from the user's device. This visual data consists of images and videos containing information to understand the living environment and living conditions. Simultaneously, the device also receives auditory data provided as audio, which the server converts into text data. This auditory data is used to understand the user's lifestyle and preferences regarding their place of residence.

[0540] The server then analyzes the aggregated visual and textual data, employing methods to extract characteristics of living conditions and lifestyles. This analysis utilizes generative AI models to effectively identify patterns in the data.

[0541] Based on the analysis results, the server selects potential relocation sites that meet the user's needs. Information about the selected sites is presented to the user via a terminal. Furthermore, it controls a program that provides a virtual reality experience through visual devices, allowing the user to virtually experience the candidate sites. These visual devices include smart glasses and head-mounted displays.

[0542] This allows users to gain a more concrete understanding of their chosen relocation destination and visualize what it would be like to actually live there. Specifically, for example, users can experience the beautiful scenery, shopping streets, and diverse facilities of the region through virtual tours.

[0543] When giving instructions to the generative AI model, a prompt such as "Create a 360-degree panoramic video and audio guide for visiting a shopping street in Nagano Prefecture" is used. This enhances the quality of the user experience and supports the selection of the optimal relocation destination.

[0544] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0545] Step 1:

[0546] Users input visual data, such as photos of their home and its surroundings, into the device. They also record audio data, such as voice recordings of their and their family's desired future living environment. Furthermore, they input text data, such as information about their current lifestyle and consumption trends. All of this data is aggregated on the device.

[0547] Step 2:

[0548] The terminal sends aggregated visual, auditory, and text data to the server. The server uses speech recognition technology to convert the received auditory data into text data. This conversion allows the user's lifestyle and housing requirements to be expressed in written form.

[0549] Step 3:

[0550] The server analyzes the converted text and visual data and uses a generative AI model to extract characteristics of living conditions and lifestyles. This analysis process considers parameters such as population density, green space area, and living infrastructure. The output is a set of characteristics designed to meet user needs.

[0551] Step 4:

[0552] Based on the analysis results, the server selects the most suitable relocation destination for the user's needs. The selection process utilizes a nationwide database of local areas, specifically considering factors such as cost of living, environmental resources, and regional cultural characteristics.

[0553] Step 5:

[0554] The server presents information about the selected relocation sites to the user using visual devices. Through a terminal connected to smart glasses or a head-mounted display, the user can virtually experience the selected region. At this stage, 360-degree panoramic video and audio guidance are provided.

[0555] Step 6:

[0556] After a customized virtual experience, users provide opinions and feedback on the selected region via their device. The server receives this feedback, re-evaluates the criteria, and proposes new potential relocation sites, thereby providing more accurate recommendations.

[0557] 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.

[0558] This invention is a system that highly personalizes the individual's relocation destination selection process by combining an emotion engine that recognizes the user's emotions. In addition to conventional data analysis, this system takes into account the user's emotional state, making it possible to suggest more appropriate and satisfying relocation destinations.

[0559] First, the user takes photos of their home and its surroundings using the device, and inputs information about their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device utilizes an emotion engine to recognize the user's emotional state from the audio and image data.

[0560] The device sends the collected data to the server as a single dataset. The server converts the audio data into text and analyzes the image data to extract characteristics of the living environment. Meanwhile, the user's emotional state (e.g., joy, surprise, anxiety) analyzed by the emotion engine is also evaluated and linked to the individual data.

[0561] Based on the sentiment analysis results, the server selects the most suitable relocation destination from a nationwide regional database that best matches the user's needs and emotions. The selection criteria incorporate prioritization based on the user's emotions, aiming not only for lifestyle fit but also for the user's emotional fulfillment.

[0562] Information on the selected relocation destination, including detailed cost of living, transportation access, and local characteristics, is transmitted to the device. The device then presents this information to the user in an interactive format to encourage consideration.

[0563] For example, if a user desires a quieter environment to reduce stress, and this information is recognized as "anxiety" by the emotion engine, the server will prioritize suggesting rural areas that are considered relatively quiet. This allows the user to make a choice that is emotionally satisfying.

[0564] Subsequently, user feedback is analyzed by the emotion engine and used to create new suggestions. Specifically, the conditions can be re-evaluated based on the user's reaction to the suggested relocation destinations, and the selection criteria can be modified as needed. This ensures that suggestions that consistently meet the user's emotional needs can be provided.

[0565] The following describes the processing flow.

[0566] Step 1:

[0567] Users take photos of their home and surrounding area using smartphones or tablets and input them into the system. They also record voice data of family opinions and their own wishes on their devices, and input information about their lifestyle and consumption patterns as text.

[0568] Step 2:

[0569] The device analyzes the input image and audio data and uses an emotion engine to recognize the user's emotional state. For example, it determines emotions such as "joy," "anxiety," and "surprise" from the tone of voice and facial expressions.

[0570] Step 3:

[0571] The terminal integrates to send collected image data, audio data, text data, and analyzed sentiment data to a server. This data is converted to an appropriate format and transmitted over a secure communication channel.

[0572] Step 4:

[0573] The server receives data sent from the terminal and applies natural language processing to convert the audio data into text data. In this process, keywords and phrases extracted from the audio are also analyzed.

[0574] Step 5:

[0575] The server uses image data to analyze the characteristics of residences and living environments. For example, it extracts elements such as interior style, house size, and brightness from photographs. At the same time, it considers emotional data to identify lifestyle tendencies and desired living environments based on that data.

[0576] Step 6:

[0577] The server combines user needs and emotional data to search for the most suitable relocation destination from a nationwide regional database. In the selection process, factors such as cost of living, transportation convenience, and regional characteristics are considered, as well as elements that contribute to the user's emotional well-being.

[0578] Step 7:

[0579] The server sends the selected relocation candidates to the user's terminal along with detailed information. This information includes photos of the area, cost of living, access information, and the availability of facilities, supporting the user's relocation decision.

[0580] Step 8:

[0581] The terminal displays information about potential relocation destinations received from the server to the user. The display is interactive, allowing the user to compare the advantages and disadvantages of each candidate location in detail.

[0582] Step 9:

[0583] Based on the information provided, users input feedback about each candidate location into their device. This feedback may include requests for more detailed information or suggestions to readjust the selection criteria.

[0584] Step 10:

[0585] The server receives feedback from the user and re-analyzes it using an emotion engine to evaluate the emotional state during the feedback process. Based on these results, it re-evaluates the conditions and generates and re-proposes new migration destination candidates.

[0586] (Example 2)

[0587] 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."

[0588] In modern society, selecting a relocation destination based on an individual's lifestyle and emotions is complex, and traditional data analysis methods struggle to provide recommendations that take emotional satisfaction into account. Furthermore, there is a need to process diverse user data formats quickly and securely.

[0589] 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.

[0590] In this invention, the server includes means for receiving image data, audio data, and text data from an individual's terminal; means for evaluating the user's emotional state using an emotion analysis engine and linking it to individual data; and means for integrating multiple data formats, generating a dataset including the emotion analysis results, and transmitting it securely. This enables personalized relocation suggestions that take into account the user's emotional satisfaction.

[0591] A "terminal" is a device operated by a user and is used to collect, input, and display information.

[0592] "Image data" refers to data that represents visual information in a digital format and is acquired using devices such as cameras.

[0593] "Audio data" refers to data that records the user's voice or sound as a digital signal and converts it into a format that can be processed.

[0594] "Text data" refers to data that represents character information in a digital format and is generated through user input.

[0595] A "sentiment analysis engine" is a software module that automatically analyzes a user's emotional state using nonverbal cues extracted from voice and image data.

[0596] A "dataset" is a collection of data that integrates various types of collected and processed data, and is used for analysis and transmission.

[0597] "Security" refers to the technologies and measures used to protect the confidentiality, integrity, and availability of data, and to prevent unauthorized access and data breaches.

[0598] "Destination" refers to the region or housing options that the user is considering for their new residence.

[0599] This invention relates to a system that suggests suitable relocation destinations based on a user's emotions and lifestyle. This system is implemented using a combination of hardware and software, including a terminal, an emotion analysis engine, image recognition technology, a natural language processing module, and security measures.

[0600] The user uses the device to photograph their home and surrounding environment, and inputs their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device uses an emotion analysis engine to analyze the user's emotional state from the audio and image data. The emotion analysis engine evaluates nonverbal cues such as the user's utterances, tone of voice, and facial expressions, and identifies the user's emotional state as "joy," "surprise," or "anxiety."

[0601] The collected data is transmitted to the server via a secure protocol. The server uses a natural language processing module to convert the audio data into text and image recognition technology to analyze the characteristics of the living environment. Emotional states are also linked to this data.

[0602] The server integrates sentiment analysis results and lifestyle information, and uses a relocation destination selection algorithm to select a suitable relocation destination from a nationwide database based on the user's preferences. The selection process takes into account user emotional priorities, and suggestions are made to enhance user satisfaction.

[0603] Information on the selected relocation destination, including detailed living costs, transportation access, and local characteristics, is transmitted to the device and presented to the user in an interactive format.

[0604] For example, if a user wants to reduce stress and this emotional state is recognized as "anxiety," the server will prioritize suggesting quiet, rural areas. This process allows the user to make emotionally satisfying choices.

[0605] (Example of a prompt message)

[0606] "If a user desires a quiet environment, but this is perceived as a feeling of anxiety, what kind of relocation destination would be appropriate?"

[0607] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0608] Step 1:

[0609] Users use their devices to photograph their homes and surrounding environments and input information about their lifestyles and consumption trends in text format. Image and text data are collected using the device's camera and keyboard or touchscreen. Furthermore, they record their family's opinions and their own thoughts as audio data. Thus, the input data includes images, text, and audio.

[0610] Step 2:

[0611] The terminal converts the collected audio data into text data using a natural language processing module. This process involves analyzing the audio signal, extracting linguistic features, and converting them into corresponding text. The output is the audio data converted into text format.

[0612] Step 3:

[0613] The device uses an emotion analysis engine to analyze audio and image data and evaluate the user's emotional state. This analysis process extracts nonverbal cues from the tone of voice and facial expressions in the images, classifying emotions into categories such as "joy," "surprise," and "anxiety." The output is the analyzed emotional state.

[0614] Step 4:

[0615] The terminal integrates the collected and analyzed data into a single dataset and sends it to the server via a secure protocol. At this stage, the input images, text, and analysis results are securely packaged and sent out. The integrated dataset arrives at the server as output.

[0616] Step 5:

[0617] The server uses image recognition technology to extract characteristics of the living environment based on the incoming dataset. Simultaneously, it combines sentiment analysis results with text information to select a relocation destination suitable for the user's lifestyle and emotions. The selection process includes analyzing multidimensional data correlations to identify the most matching region. The output is the selected relocation destination.

[0618] Step 6:

[0619] The server sends detailed information about the selected relocation destination to the terminal. This information includes cost of living, transportation access, and local characteristics, enabling the user to make an informed decision. This output interactively provides the user with the information they want to know.

[0620] Step 7:

[0621] The user provides feedback on the presented relocation information. The device then analyzes this feedback again using a sentiment analysis engine and sends the results to the server. Further user desires and dissatisfactions are collected from the feedback input as text or audio data.

[0622] Step 8:

[0623] The server uses the collected feedback to re-evaluate existing data assessments and, if necessary, generate new migration destination suggestions. Here, the sentiment factors obtained from the feedback are incorporated as a new dataset and the re-evaluation process is performed. As output, improved migration destination suggestions are provided.

[0624] (Application Example 2)

[0625] 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."

[0626] In modern commercial facilities and sales environments, accurately understanding customer emotions and needs and making appropriate suggestions on the spot presents a challenge. In such situations, the customer experience may not be optimized, potentially leading to lost sales opportunities. Therefore, there is a need to sense customer reactions in real time and provide personalized product suggestions accordingly.

[0627] 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.

[0628] In this invention, the server includes means for receiving image data, voice data, and text data input by an individual; means for converting voice information into text information; means for analyzing the image data and text data to extract characteristics of the living environment and lifestyle; means for recognizing the user's emotional state and selecting candidates that match the user's emotions and needs; means for suggesting products based on the user's emotional analysis; and means for presenting the selected product or regional information to the user. This enables accurate product suggestions based on the customer's emotional state, improving the sales experience and reducing lost opportunities.

[0629] "Image data" refers to digital data that includes visual information entered by an individual.

[0630] "Audio data" refers to information recorded as digital signals of sounds emitted by an individual.

[0631] "Text data" refers to digital information in the form of written characters or sentences.

[0632] "Means of converting audio information into text information" refers to processing devices or software used to convert audio data into text data.

[0633] "Means for extracting characteristics of living environments and lifestyles" refers to technologies that analyze living environments and behavioral patterns from input data to identify their characteristics.

[0634] "Recognizing the user's emotional state" is the process of determining the type and intensity of emotions from the user's input data.

[0635] "Means of selecting candidates" refers to the process of presenting options that match the user's emotions and needs.

[0636] "Means of proposing products" refers to methods for presenting products suitable for customers based on analyzed data.

[0637] "Means of presenting information to the user" refers to devices or systems that inform the user of selected information visually or audibly.

[0638] This invention can be implemented as a customer suggestion system in a sales environment utilizing smart glasses. The server receives image data, audio data, and text data collected by the smart glasses. Smart glasses may include devices such as Google Glass. Audio data is converted into text data using on-device emotion recognition software and sent to a cloud service such as Microsoft Azure Cognition Services.

[0639] The server utilizes image and text data to analyze the customer's living environment and lifestyle, extracting its characteristics. Furthermore, it identifies the customer's emotional state through an emotion engine and selects product candidates that are suitable for the customer's needs based on this information.

[0640] The selected product information is displayed on the smart glasses' screen, and the salesperson can suggest or explain it to the customer. For example, if the customer's facial expression indicates anxiety, the system can suggest an aromatherapy candle as a stress-relieving product.

[0641] The user's reaction to this suggestion is also analyzed by the emotion engine and sent to the server. Based on the user's feedback, the server optimizes the suggestion and generates new product candidates.

[0642] An example of a specific prompt for a generative AI model is: "I would like advice on which products in the store to recommend when a customer appears anxious." By using this prompt, the system can instantly respond to diverse customer needs and realize a highly personalized sales strategy.

[0643] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0644] Step 1:

[0645] The device collects image and audio data from the customer through smart glasses. This records the customer's facial expressions and the moment they speak. The input is image and audio, and the raw data is stored in the device as output.

[0646] Step 2:

[0647] The device performs the process of converting audio data into text data. Using speech recognition software, it analyzes the recorded audio data and converts it into text. This allows the content of the audio to be obtained as text information.

[0648] Step 3:

[0649] The server analyzes the received image and text data. Using AI image analysis technology, emotions are extracted from the customer's facial expressions and movements. The text data is understood through natural language processing. The output of this step is information about the customer's emotional state and lifestyle.

[0650] Step 4:

[0651] The server performs preprocessing, and the emotion engine analyzes the emotional state in detail. A generative AI model is used to quantify the user's emotions and optimize candidate products. The input is analyzed data, and the output is a recommendation algorithm based on the emotional state.

[0652] Step 5:

[0653] The server generates product suggestions tailored to the user's emotions and needs based on the analysis results and sends them to the terminal. The products presented are aligned with the customer's emotional state, aiming to provide an optimal purchasing experience.

[0654] Step 6:

[0655] Users interactively receive results and make selections and provide feedback on the displayed products. They view product information on the smart glasses display, and their responses are recorded based on their satisfaction level.

[0656] Step 7:

[0657] The device sends the user's response back to the server. This feedback is necessary for generating new suggestions and, after sentiment analysis, becomes input for the next step. The server continuously improves the system based on the collected feedback.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] [Fourth Embodiment]

[0662] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0663] 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.

[0664] 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).

[0665] 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.

[0666] 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.

[0667] 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).

[0668] 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.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] 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".

[0675] This invention is a system that promotes migration to rural areas to solve the problem of over-concentration in urban areas, and it uses image data, voice data, and text data to suggest the most suitable relocation destination for an individual. The system's program processing is described below in natural language.

[0676] First, users input photos of their home and surrounding area into their device and record voice data about their desired future living environment for themselves and their family. They also input information about their current lifestyle and consumption trends in text format. This data is collected and integrated by the user's device.

[0677] The terminal sends the aggregated data to the server. The server converts the voice data into text data and analyzes all the data. Specifically, the server uses image data to evaluate the characteristics of the residence and extracts the user's lifestyle and living environment preferences from the voice and text data.

[0678] Based on the results, the server searches a nationwide database of local areas and generates potential relocation destinations that match the user's needs. The server then sends additional information, such as cost of living, convenience, and regional characteristics, to the terminal.

[0679] The terminal presents information received from the server to the user, displaying it interactively in an easy-to-understand format. The user can review this information and provide feedback. The server receives feedback from the user, re-evaluates the conditions, and can then suggest new candidate locations.

[0680] For example, if a user lives in an urban area and prioritizes raising children in a nature-rich environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential rural locations. Furthermore, it will provide detailed information on housing costs and living infrastructure in those areas, helping the user consider a concrete relocation plan. Through this process, users can find a relocation destination that is optimized for their wishes and needs.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] Users take photos of their home and surrounding area and save them to their device using their smartphone or camera. They also record voice data based on their and their family's wishes and input information about their current lifestyle and consumption trends in text format.

[0684] Step 2:

[0685] The terminal integrates the image, audio, and text data entered by the user into a single dataset and prepares it for transmission to the server. The data undergoes preprocessing, such as format conversion.

[0686] Step 3:

[0687] The terminal sends the prepared data to the server and simultaneously notifies the user of the transmission progress. After the transmission is complete, the user is shown a message prompting them to proceed to the next step.

[0688] Step 4:

[0689] The server receives data sent from the terminal and performs a speech recognition process to convert the audio data into text data. It then integrates the results with other data.

[0690] Step 5:

[0691] The server analyzes the integrated dataset and extracts features of the living environment (e.g., house size, room layout) from the image data. Similarly, it uses the converted text data to identify the user's lifestyle and desired living environment requirements.

[0692] Step 6:

[0693] Based on the analysis results, the server references a nationwide database of local areas and selects multiple potential relocation destinations that match the user's needs. It also searches for detailed information related to each candidate (such as cost of living, transportation access, and regional characteristics).

[0694] Step 7:

[0695] The server sends the selected migration destination candidates and their detailed information to the terminal. This prepares the terminal to present this information to the user.

[0696] Step 8:

[0697] The device visually presents the received information on potential relocation destinations to the user in an interactive format. The user can review this information and view detailed content related to selecting a relocation destination.

[0698] Step 9:

[0699] The user enters feedback about the presented candidate locations into the device. This feedback may include requests for further adjustments to the conditions or requests for alternative options.

[0700] Step 10:

[0701] The server receives feedback from the user and initiates a process of re-evaluating the conditions. If necessary, it generates and re-proposes new migration destinations.

[0702] (Example 1)

[0703] 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".

[0704] The challenge lies in providing an effective support system to alleviate urban overcrowding and promote optimal rural migration for individuals. In particular, there is a need to be able to quickly and accurately propose suitable relocation destinations based on individual lifestyles and preferences.

[0705] 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.

[0706] In this invention, the server includes means for receiving diverse data input by an individual, means for performing data analysis using technology to convert voice data into text data, and means for evaluating the characteristics of image data and text data to extract features of the living environment and lifestyle. This makes it possible to easily determine the optimal relocation destination based on the user's requests.

[0707] "Diverse data" refers to data that includes information in different formats, such as image data, audio data, and text data.

[0708] "Technology for converting audio data into text data" refers to automatic speech recognition technology that converts speech into text information, thereby making audio input into a text format that can be analyzed.

[0709] "Characteristics of the living environment and lifestyle" refers to characteristics related to the place of residence and lifestyle, and includes the structure of the dwelling, the surrounding environment, and lifestyle habits.

[0710] "A relocation destination that meets the user's needs" refers to a new place of residence selected in light of the user's specific needs and desires.

[0711] "Providing information visually" means displaying information to users in an easy-to-understand manner using images and graphics.

[0712] "Receiving responses, re-evaluating requirements, and generating new relocation options" refers to the process of reviewing conditions based on feedback provided by users and proposing new potential relocation destinations.

[0713] "Integrating data in different formats" refers to the process of unifying data expressed in multiple formats and combining them into a form that can be used effectively.

[0714] "Maintaining the security of information and transmitting it to the processing device" means transmitting data to the processing device while maintaining the confidentiality and integrity of the data.

[0715] This invention relates to a system that suggests the optimal relocation destination based on an individual's lifestyle and desired living environment. This system includes terminals, servers, and communication means connecting them.

[0716] Users take photos of their homes using their devices, inputting visual data of the interior and surrounding environment. Simultaneously, they record audio data to provide information about their desired living environment and lifestyle. They can also input detailed information about their current habits and consumption trends as text data. This data is integrated on the device and transmitted to the server using a secure protocol.

[0717] The server processes data using various conversion and analysis techniques. Specifically, it uses automatic speech recognition (ASR) technology to convert speech data into text data. This technology can utilize voice services from common cloud infrastructures. The server also analyzes visual data using image analysis technology to evaluate living characteristics. Furthermore, it uses natural language processing (NLP) technology to analyze text data and extract the user's lifestyle and preferences. Widely used AI libraries and APIs can be utilized for these technologies.

[0718] The server uses a generative AI model, based on features extracted from the user, to search a nationwide regional database and generate optimal relocation destinations. This candidate location data includes factors such as cost of living, convenience, and regional characteristics. The generated information is then sent back to the terminal.

[0719] The terminal interactively presents the user with potential relocation destinations received from the server. This display is presented visually in map or list format, allowing the user to view and select detailed information. User feedback is sent back to the server and used to re-evaluate the conditions and generate new potential locations.

[0720] For example, if a user lives in an urban area and desires to raise their children in a rich natural environment, the system will suggest areas with abundant nature and well-developed educational facilities as potential options. This allows the user to compare and consider detailed housing costs and living infrastructure information, and then formulate a concrete relocation plan.

[0721] An example of a prompt message is: "Create a system that suggests the optimal relocation destination based on the user's desired living environment and lifestyle. Specific conditions should include a rich natural environment, excellent educational facilities, and low cost of living."

[0722] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0723] Step 1:

[0724] Users take photos of their home and surroundings using a device and input them as digital data. They also record information about their desired living environment and lifestyle using voice input, generating audio data that can be converted into text. Furthermore, they input their daily habits and consumption trends as text. As a result, image data, audio data, and text data are aggregated on the device.

[0725] Step 2:

[0726] The device sends the aggregated data to the server using the SSL / TLS protocol. The data sent includes images, audio, and text that detail the user's preferences. Data confidentiality and integrity are maintained throughout this process. After transmission, the device notifies the user of the completion of the transmission.

[0727] Step 3:

[0728] The server converts the received audio data into text data using automatic speech recognition (ASR) technology. Specifically, it analyzes the audio waveform using a speech recognition API and outputs the corresponding text. As a result, the information obtained from the audio is stored on the server as text data.

[0729] Step 4:

[0730] The server analyzes the received image data using image analysis technology to evaluate the characteristics of the living space. This involves using AI models to recognize objects and scenes within the image. This process yields feature information extracted from the image.

[0731] Step 5:

[0732] The server analyzes the converted audio and text data using natural language processing (NLP) techniques to extract the user's lifestyle and living environment preferences. The NLP model understands key keywords and context from the input data and converts them into quantifiable data.

[0733] Step 6:

[0734] Based on the analysis results, the server uses a generative AI model to search a nationwide regional database and generate potential relocation destinations that match the user's requirements. The generative AI model matches the user's desired characteristics with the characteristics of the region to select the most suitable candidate location. As a result, a list of highly suitable relocation destinations is generated on the server.

[0735] Step 7:

[0736] The server collects additional information, including cost of living, convenience, and local characteristics, and sends it to the user's terminal along with a curated list of potential relocation destinations. This information is presented in a format that is intuitively understandable to the user.

[0737] Step 8:

[0738] The terminal presents the user with candidate location information received from the server. This information is displayed in interactive map or list formats, allowing the user to examine details. This enables the user to compare and select from various candidate locations.

[0739] Step 9:

[0740] The user reviews the information on the presented candidate locations and provides feedback. This feedback may include reasons for selection and changes to the criteria. The device sends the feedback to the server, and the user's opinions are incorporated.

[0741] Step 10:

[0742] The server re-evaluates the conditions using user feedback and generates new potential relocation destinations as needed. The re-evaluation process is carried out to enable the presentation of more accurate candidate locations and to provide the optimal plan according to the user's needs.

[0743] (Application Example 1)

[0744] 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".

[0745] There is a challenge in mitigating the problem of over-concentration in urban areas by promoting migration to rural areas by providing individuals considering relocation with specific information about living environments. However, simply presenting data is not effective support, as users cannot fully understand the appeal of their relocation destination or imagine what life would actually be like there. Furthermore, there is a need to further improve the accuracy of selecting relocation destinations that are suitable for the user's needs.

[0746] 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.

[0747] In this invention, the server includes means for receiving visual data, auditory data, and text data input by an individual; means for converting auditory data into text data; means for analyzing the visual data and text data to extract characteristics of living conditions and lifestyles; means for selecting potential relocation sites that suit the user's needs; means for presenting information on the selected relocation sites to the user; and means for controlling a visual device for providing a virtual experience of the selected relocation sites. This makes it possible for the user to form a more concrete image of their relocation destination and simulate actual life there.

[0748] "Visual data" refers to data, including images and videos, provided by individuals, and serves as a source of information for understanding living conditions and characteristics of the living environment.

[0749] "Auditory data" refers to data provided by individuals in audio format, which can serve as clues to extract information about users' lifestyles and housing preferences.

[0750] "Text data" refers to data entered by users as text, and includes detailed information about lifestyle patterns and consumption trends.

[0751] A "visual device" is a hardware device that provides users with a virtual reality experience and helps them understand the selected potential relocation sites more concretely.

[0752] The system based on this invention has the function of suggesting the most suitable relocation destination to the user using visual, auditory, and textual data provided by the individual. The system is configured as follows:

[0753] The server receives visual data from the user's device. This visual data consists of images and videos containing information to understand the living environment and living conditions. Simultaneously, the device also receives auditory data provided as audio, which the server converts into text data. This auditory data is used to understand the user's lifestyle and preferences regarding their place of residence.

[0754] The server then analyzes the aggregated visual and textual data, employing methods to extract characteristics of living conditions and lifestyles. This analysis utilizes generative AI models to effectively identify patterns in the data.

[0755] Based on the analysis results, the server selects potential relocation sites that meet the user's needs. Information about the selected sites is presented to the user via a terminal. Furthermore, it controls a program that provides a virtual reality experience through visual devices, allowing the user to virtually experience the candidate sites. These visual devices include smart glasses and head-mounted displays.

[0756] This allows users to gain a more concrete understanding of their chosen relocation destination and visualize what it would be like to actually live there. Specifically, for example, users can experience the beautiful scenery, shopping streets, and diverse facilities of the region through virtual tours.

[0757] When giving instructions to the generative AI model, a prompt such as "Create a 360-degree panoramic video and audio guide for visiting a shopping street in Nagano Prefecture" is used. This enhances the quality of the user experience and supports the selection of the optimal relocation destination.

[0758] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0759] Step 1:

[0760] Users input visual data, such as photos of their home and its surroundings, into the device. They also record audio data, such as voice recordings of their and their family's desired future living environment. Furthermore, they input text data, such as information about their current lifestyle and consumption trends. All of this data is aggregated on the device.

[0761] Step 2:

[0762] The terminal sends aggregated visual, auditory, and text data to the server. The server uses speech recognition technology to convert the received auditory data into text data. This conversion allows the user's lifestyle and housing requirements to be expressed in written form.

[0763] Step 3:

[0764] The server analyzes the converted text and visual data and uses a generative AI model to extract characteristics of living conditions and lifestyles. This analysis process considers parameters such as population density, green space area, and living infrastructure. The output is a set of characteristics designed to meet user needs.

[0765] Step 4:

[0766] Based on the analysis results, the server selects the most suitable relocation destination for the user's needs. The selection process utilizes a nationwide database of local areas, specifically considering factors such as cost of living, environmental resources, and regional cultural characteristics.

[0767] Step 5:

[0768] The server presents information about the selected relocation sites to the user using visual devices. Through a terminal connected to smart glasses or a head-mounted display, the user can virtually experience the selected region. At this stage, 360-degree panoramic video and audio guidance are provided.

[0769] Step 6:

[0770] After a customized virtual experience, users provide opinions and feedback on the selected region via their device. The server receives this feedback, re-evaluates the criteria, and proposes new potential relocation sites, thereby providing more accurate recommendations.

[0771] 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.

[0772] This invention is a system that highly personalizes the individual's relocation destination selection process by combining an emotion engine that recognizes the user's emotions. In addition to conventional data analysis, this system takes into account the user's emotional state, making it possible to suggest more appropriate and satisfying relocation destinations.

[0773] First, the user takes photos of their home and its surroundings using the device, and inputs information about their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device utilizes an emotion engine to recognize the user's emotional state from the audio and image data.

[0774] The device sends the collected data to the server as a single dataset. The server converts the audio data into text and analyzes the image data to extract characteristics of the living environment. Meanwhile, the user's emotional state (e.g., joy, surprise, anxiety) analyzed by the emotion engine is also evaluated and linked to the individual data.

[0775] Based on the sentiment analysis results, the server selects the most suitable relocation destination from a nationwide regional database that best matches the user's needs and emotions. The selection criteria incorporate prioritization based on the user's emotions, aiming not only for lifestyle fit but also for the user's emotional fulfillment.

[0776] Information on the selected relocation destination, including detailed cost of living, transportation access, and local characteristics, is transmitted to the device. The device then presents this information to the user in an interactive format to encourage consideration.

[0777] For example, if a user desires a quieter environment to reduce stress, and this information is recognized as "anxiety" by the emotion engine, the server will prioritize suggesting rural areas that are considered relatively quiet. This allows the user to make a choice that is emotionally satisfying.

[0778] Subsequently, user feedback is analyzed by the emotion engine and used to create new suggestions. Specifically, the conditions can be re-evaluated based on the user's reaction to the suggested relocation destinations, and the selection criteria can be modified as needed. This ensures that suggestions that consistently meet the user's emotional needs can be provided.

[0779] The following describes the processing flow.

[0780] Step 1:

[0781] Users take photos of their home and surrounding area using smartphones or tablets and input them into the system. They also record voice data of family opinions and their own wishes on their devices, and input information about their lifestyle and consumption patterns as text.

[0782] Step 2:

[0783] The device analyzes the input image and audio data and uses an emotion engine to recognize the user's emotional state. For example, it determines emotions such as "joy," "anxiety," and "surprise" from the tone of voice and facial expressions.

[0784] Step 3:

[0785] The terminal integrates to send collected image data, audio data, text data, and analyzed sentiment data to a server. This data is converted to an appropriate format and transmitted over a secure communication channel.

[0786] Step 4:

[0787] The server receives data sent from the terminal and applies natural language processing to convert the audio data into text data. In this process, keywords and phrases extracted from the audio are also analyzed.

[0788] Step 5:

[0789] The server uses image data to analyze the characteristics of residences and living environments. For example, it extracts elements such as interior style, house size, and brightness from photographs. At the same time, it considers emotional data to identify lifestyle tendencies and desired living environments based on that data.

[0790] Step 6:

[0791] The server combines user needs and emotional data to search for the most suitable relocation destination from a nationwide regional database. In the selection process, factors such as cost of living, transportation convenience, and regional characteristics are considered, as well as elements that contribute to the user's emotional well-being.

[0792] Step 7:

[0793] The server sends the selected relocation candidates to the user's terminal along with detailed information. This information includes photos of the area, cost of living, access information, and the availability of facilities, supporting the user's relocation decision-making.

[0794] Step 8:

[0795] The terminal displays information about potential relocation destinations received from the server to the user. The display is interactive, allowing the user to compare the advantages and disadvantages of each candidate location in detail.

[0796] Step 9:

[0797] Based on the information provided, users input feedback about each candidate location into their device. This feedback may include requests for more detailed information or suggestions to readjust the selection criteria.

[0798] Step 10:

[0799] The server receives feedback from the user and re-analyzes it using an emotion engine to evaluate the emotional state during the feedback process. Based on these results, it re-evaluates the conditions and generates and re-proposes new migration destination candidates.

[0800] (Example 2)

[0801] 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".

[0802] In modern society, selecting a relocation destination based on an individual's lifestyle and emotions is complex, and traditional data analysis methods struggle to provide recommendations that take emotional satisfaction into account. Furthermore, there is a need to process diverse user data formats quickly and securely.

[0803] 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.

[0804] In this invention, the server includes means for receiving image data, audio data, and text data from an individual's terminal; means for evaluating the user's emotional state using an emotion analysis engine and linking it to individual data; and means for integrating multiple data formats, generating a dataset including the emotion analysis results, and transmitting it securely. This enables personalized relocation suggestions that take into account the user's emotional satisfaction.

[0805] A "terminal" is a device operated by a user and is used to collect, input, and display information.

[0806] "Image data" refers to data that represents visual information in a digital format and is acquired using devices such as cameras.

[0807] "Audio data" refers to data that records the user's voice or sound as a digital signal and converts it into a format that can be processed.

[0808] "Text data" refers to data that represents character information in a digital format and is generated through user input.

[0809] A "sentiment analysis engine" is a software module that automatically analyzes a user's emotional state using nonverbal cues extracted from voice and image data.

[0810] A "dataset" is a collection of data that integrates various types of collected and processed data, and is used for analysis and transmission.

[0811] "Security" refers to the technologies and measures used to protect the confidentiality, integrity, and availability of data, and to prevent unauthorized access and data breaches.

[0812] "Destination" refers to the region or housing options that the user is considering for their new residence.

[0813] This invention relates to a system that suggests suitable relocation destinations based on a user's emotions and lifestyle. This system is implemented using a combination of hardware and software, including a terminal, an emotion analysis engine, image recognition technology, a natural language processing module, and security measures.

[0814] The user uses the device to photograph their home and surrounding environment, and inputs their lifestyle and consumption habits in text format. Furthermore, they record their family's opinions and their own thoughts as audio data. At this stage, the device uses an emotion analysis engine to analyze the user's emotional state from the audio and image data. The emotion analysis engine evaluates nonverbal cues such as the user's utterances, tone of voice, and facial expressions, and identifies the user's emotional state as "joy," "surprise," or "anxiety."

[0815] The collected data is transmitted to the server via a secure protocol. The server uses a natural language processing module to convert the audio data into text and image recognition technology to analyze the characteristics of the living environment. Emotional states are also linked to this data.

[0816] The server integrates sentiment analysis results and lifestyle information, and uses a relocation destination selection algorithm to select a suitable relocation destination from a nationwide database based on the user's preferences. The selection process takes into account user emotional priorities, and suggestions are made to enhance user satisfaction.

[0817] Information on the selected relocation destination, including detailed living costs, transportation access, and local characteristics, is transmitted to the device and presented to the user in an interactive format.

[0818] For example, if a user wants to reduce stress and this emotional state is recognized as "anxiety," the server will prioritize suggesting quiet, rural areas. This process allows the user to make emotionally satisfying choices.

[0819] (Example of a prompt message)

[0820] "If a user desires a quiet environment, but this is perceived as a feeling of anxiety, what kind of relocation destination would be appropriate?"

[0821] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0822] Step 1:

[0823] Users use their devices to photograph their homes and surrounding environments and input information about their lifestyles and consumption trends in text format. Image and text data are collected using the device's camera and keyboard or touchscreen. Furthermore, they record their family's opinions and their own thoughts as audio data. Thus, the input data includes images, text, and audio.

[0824] Step 2:

[0825] The terminal converts the collected audio data into text data using a natural language processing module. This process involves analyzing the audio signal, extracting linguistic features, and converting them into corresponding text. The output is the audio data converted into text format.

[0826] Step 3:

[0827] The device uses an emotion analysis engine to analyze audio and image data and evaluate the user's emotional state. This analysis process extracts nonverbal cues from the tone of voice and facial expressions in the images, classifying emotions into categories such as "joy," "surprise," and "anxiety." The output is the analyzed emotional state.

[0828] Step 4:

[0829] The terminal integrates the collected and analyzed data into a single dataset and sends it to the server via a secure protocol. At this stage, the input images, text, and analysis results are securely packaged and sent out. The integrated dataset arrives at the server as output.

[0830] Step 5:

[0831] The server uses image recognition technology to extract characteristics of the living environment based on the incoming dataset. Simultaneously, it combines sentiment analysis results with text information to select a relocation destination suitable for the user's lifestyle and emotions. The selection process includes analyzing multidimensional data correlations to identify the most matching region. The output is the selected relocation destination.

[0832] Step 6:

[0833] The server sends detailed information about the selected relocation destination to the terminal. This information includes cost of living, transportation access, and local characteristics, enabling the user to make an informed decision. This output interactively provides the user with the information they want to know.

[0834] Step 7:

[0835] The user provides feedback on the presented relocation information. The device then analyzes this feedback again using a sentiment analysis engine and sends the results to the server. Further user desires and dissatisfactions are collected from the feedback input as text or audio data.

[0836] Step 8:

[0837] The server uses the collected feedback to re-evaluate existing data assessments and, if necessary, generate new migration destination suggestions. Here, the sentiment factors obtained from the feedback are incorporated as a new dataset and the re-evaluation process is performed. As output, improved migration destination suggestions are provided.

[0838] (Application Example 2)

[0839] 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".

[0840] In modern commercial facilities and sales environments, accurately understanding customer emotions and needs and making appropriate suggestions on the spot presents a challenge. In such situations, the customer experience may not be optimized, potentially leading to lost sales opportunities. Therefore, there is a need to sense customer reactions in real time and provide personalized product suggestions accordingly.

[0841] 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.

[0842] In this invention, the server includes means for receiving image data, voice data, and text data input by an individual; means for converting voice information into text information; means for analyzing the image data and text data to extract characteristics of the living environment and lifestyle; means for recognizing the user's emotional state and selecting candidates that match the user's emotions and needs; means for suggesting products based on the user's emotional analysis; and means for presenting the selected product or regional information to the user. This enables accurate product suggestions based on the customer's emotional state, improving the sales experience and reducing lost opportunities.

[0843] "Image data" refers to digital data that includes visual information entered by an individual.

[0844] "Audio data" refers to information recorded as digital signals of sounds emitted by an individual.

[0845] "Text data" refers to digital information in the form of written characters or sentences.

[0846] "Means of converting audio information into text information" refers to processing devices or software used to convert audio data into text data.

[0847] "Means for extracting characteristics of living environments and lifestyles" refers to technologies that analyze living environments and behavioral patterns from input data to identify their characteristics.

[0848] "Recognizing the user's emotional state" is the process of determining the type and intensity of emotions from the user's input data.

[0849] "Means of selecting candidates" refers to the process of presenting options that match the user's emotions and needs.

[0850] "Means of proposing products" refers to methods for presenting products suitable for customers based on analyzed data.

[0851] "Means of presenting information to the user" refers to devices or systems that inform the user of selected information visually or audibly.

[0852] This invention can be implemented as a customer suggestion system in a sales environment utilizing smart glasses. The server receives image data, audio data, and text data collected by the smart glasses. Smart glasses may include devices such as Google Glass. Audio data is converted into text data using on-device emotion recognition software and sent to a cloud service such as Microsoft Azure Cognition Services.

[0853] The server utilizes image and text data to analyze the customer's living environment and lifestyle, extracting its characteristics. Furthermore, it identifies the customer's emotional state through an emotion engine and selects product candidates that are suitable for the customer's needs based on this information.

[0854] The selected product information is displayed on the smart glasses' screen, and the salesperson can suggest or explain it to the customer. For example, if the customer's facial expression indicates anxiety, the system can suggest an aromatherapy candle as a stress-relieving product.

[0855] The user's reaction to this suggestion is also analyzed by the emotion engine and sent to the server. Based on the user's feedback, the server optimizes the suggestion and generates new product candidates.

[0856] An example of a specific prompt for a generative AI model is: "I would like advice on which products in the store to recommend when a customer appears anxious." By using this prompt, the system can instantly respond to diverse customer needs and realize a highly personalized sales strategy.

[0857] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0858] Step 1:

[0859] The device collects image and audio data from the customer through smart glasses. This records the customer's facial expressions and the moment they speak. The input is image and audio, and the raw data is stored in the device as output.

[0860] Step 2:

[0861] The device performs the process of converting audio data into text data. Using speech recognition software, it analyzes the recorded audio data and converts it into text. This allows the content of the audio to be obtained as text information.

[0862] Step 3:

[0863] The server analyzes the received image and text data. Using AI image analysis technology, emotions are extracted from the customer's facial expressions and movements. The text data is understood through natural language processing. The output of this step is information about the customer's emotional state and lifestyle.

[0864] Step 4:

[0865] The server performs preprocessing, and the emotion engine analyzes the emotional state in detail. A generative AI model is used to quantify the user's emotions and optimize candidate products. The input is analyzed data, and the output is a recommendation algorithm based on the emotional state.

[0866] Step 5:

[0867] The server generates product suggestions tailored to the user's emotions and needs based on the analysis results and sends them to the terminal. The products presented are aligned with the customer's emotional state, aiming to provide an optimal purchasing experience.

[0868] Step 6:

[0869] Users interactively receive results and make selections and provide feedback on the displayed products. They view product information on the smart glasses display, and their responses are recorded based on their satisfaction level.

[0870] Step 7:

[0871] The device sends the user's response back to the server. This feedback is necessary for generating new suggestions and, after sentiment analysis, becomes input for the next step. The server continuously improves the system based on the collected feedback.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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."

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] The following is further disclosed regarding the embodiments described above.

[0894] (Claim 1)

[0895] A means of receiving image data, audio data, and text data entered by an individual,

[0896] A means of converting audio data into text data,

[0897] A means for analyzing the aforementioned image data and text data and extracting characteristics of the living environment and lifestyle,

[0898] A means of selecting a relocation destination that suits the user's needs,

[0899] A means of presenting users with information about the selected relocation destination,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, comprising means for receiving user feedback, re-evaluating conditions, and generating new potential migration destinations.

[0903] (Claim 3)

[0904] The system according to claim 1, comprising means for integrating multiple data formats and transmitting them to a server while ensuring security.

[0905] "Example 1"

[0906] (Claim 1)

[0907] A means of receiving diverse data entered by individuals,

[0908] A means of performing data analysis using technology that converts audio data into text data,

[0909] A means for evaluating the characteristics of image data and text data and extracting features of the living environment and lifestyle,

[0910] A means of determining a relocation destination that suits the user's needs,

[0911] A means of visually providing users with detailed information about the chosen relocation destination,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, comprising means for receiving responses from users, re-evaluating requirements, and generating new migration destination proposals.

[0915] (Claim 3)

[0916] The system according to claim 1, comprising means for integrating data of different formats and transmitting it to a processing device while maintaining the security of the information.

[0917] "Application Example 1"

[0918] (Claim 1)

[0919] A means of receiving visual data, auditory data, and text data entered by an individual,

[0920] A means of converting auditory data into text data,

[0921] A means for analyzing the aforementioned visual data and text data to extract characteristics of living conditions and lifestyles,

[0922] A means of selecting a potential relocation site that meets the user's needs,

[0923] A means of presenting users with information on selected potential relocation sites,

[0924] A means for controlling a visual device to provide a virtual experience of selected potential relocation sites,

[0925] A system that includes this.

[0926] (Claim 2)

[0927] The system according to claim 1, comprising means for receiving user feedback, re-evaluating conditions, and generating new potential relocation sites.

[0928] (Claim 3)

[0929] The system according to claim 1, comprising means for aggregating multiple data formats and transmitting them to a server while ensuring information protection.

[0930] "Example 2 of combining an emotion engine"

[0931] (Claim 1)

[0932] A means of receiving image data, audio data, and text data from a personal device,

[0933] A means of converting audio data into text data using a natural language processing module,

[0934] A means for extracting characteristics of the living environment and lifestyle from the image data and text data by applying image recognition technology,

[0935] A means of evaluating a user's emotional state using an emotion analysis engine and linking it to individual data,

[0936] A means of selecting a relocation destination that suits the user's needs, taking into account the user's emotional state,

[0937] A means of presenting detailed information about the selected relocation destination to the user in an interactive format,

[0938] A system that includes this.

[0939] (Claim 2)

[0940] The system according to claim 1, comprising means for analyzing user feedback with an emotion analysis engine, re-evaluating conditions based on the results, and generating new migration destination candidates.

[0941] (Claim 3)

[0942] The system according to claim 1, comprising means for integrating multiple data formats, generating a dataset including sentiment analysis results, and transmitting it to a server while ensuring security.

[0943] "Application example 2 when combining with an emotional engine"

[0944] (Claim 1)

[0945] A means of receiving image data, audio data, and text data entered by an individual,

[0946] A means of converting audio information into text information,

[0947] A means for analyzing the aforementioned image data and text data and extracting characteristics of the living environment and lifestyle,

[0948] A means for recognizing the user's emotional state and selecting candidates that match the user's emotions and needs,

[0949] A method for suggesting products based on user sentiment analysis,

[0950] A means of presenting selected product or regional information to the user,

[0951] A system that includes this.

[0952] (Claim 2)

[0953] The system according to claim 1, comprising means for receiving user feedback, re-evaluating conditions, and generating new product or region candidates.

[0954] (Claim 3)

[0955] The system according to claim 1, comprising means for integrating different data formats and processing information while ensuring its security. [Explanation of Symbols]

[0956] 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 receiving image data, audio data, and text data entered by an individual, A means of converting audio data into text data, A means for analyzing the aforementioned image data and text data and extracting characteristics of the living environment and lifestyle, A means of selecting a relocation destination that suits the user's needs, A means of presenting users with information about the selected relocation destination, A system that includes this.

2. The system according to claim 1, comprising means for receiving user feedback, re-evaluating conditions, and generating new migration destination candidates.

3. The system according to claim 1, comprising means for integrating multiple data formats and transmitting them to a server while ensuring security.

Images