system

Abstract

We provide the system. [Solution] Image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings, An anonymization method that anonymizes the attribute information of identified individuals and converts it into a format that does not allow for the identification of individuals, A trend information extraction method that extracts the latest trend information collected from information sources, A content generation method that generates advertisements or information by combining anonymized personal attribute information and trend information, A display control means that outputs the generated advertisement or information to a display device, 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 character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, while consumers want to receive information suitable for themselves quickly and accurately, the protection of personal information has become a major concern. However, conventional advertising display systems have a problem that it is difficult to provide information optimized for the attributes of each passerby and real-time trends. In addition, when insufficient consideration is given to privacy, there is a risk of leakage of personal information. There is a need to solve these problems and provide personalized advertisements and information based on anonymized data.

Means for Solving the Problems

[0005] This invention provides a digital signage system that protects privacy by using an anonymization method to anonymize the attribute information generated by an image analysis method that identifies an individual's attributes such as age, gender, facial expression, clothing, and belongings. It also obtains real-time trend information by using a trend information extraction method that extracts the latest trend information collected from information sources. Furthermore, it provides a digital signage system that provides appropriate information to individual passersby in real time by combining anonymized personal attribute information and trend information to generate user-optimized advertisements or information and outputting them to a display device.

[0006] "Passersby" is a general term for people walking in public places, and refers to an unspecified number of people, not a specific individual.

[0007] "Visual information" refers to visual data acquired using cameras or other recording devices, and can be in the form of still images or videos.

[0008] "Image analysis means" refers to technology or devices for analyzing video information and identifying specific features or patterns, particularly technologies for identifying personal attributes such as age, gender, and facial expressions.

[0009] "Personal attributes" refer to information or characteristics that define an individual, such as age, gender, facial expression, clothing, and possessions.

[0010] "Anonymization means" refers to a technology or method that removes or transforms information that could identify an individual, thereby making the data non-identifiable.

[0011] "Information sources" refer to the sources used to obtain data, and these include news feeds and information exchange networks.

[0012] "Trend information extraction means" refers to techniques or methods for analyzing data collected from information sources to identify current trends and developments.

[0013] "Content generation means" refers to technologies or devices for creating advertisements or information based on specific needs or conditions, and in particular, those that construct content by combining personal attribute information and trend information.

[0014] "Display control means" refers to technology or devices that perform control for outputting generated advertisements or information to a display device.

[0015] A "display device" refers to a device used to present visual content to humans, and includes digital signage, among other things. [Brief explanation of the drawing]

[0016] [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]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a 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.

[0020] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a digital signage system for displaying optimized advertisements and information to passersby in real time. Each element works in conjunction to enable the generation and display of personalized content while avoiding the identification of personal information.

[0038] First, the terminal uses cameras installed on streets and in commercial facilities to acquire video information of passersby. This video information is transmitted to the server in real time. After receiving this video information, the server uses image analysis technology to identify personal attributes of passersby, such as age, gender, facial expression, clothing, and belongings.

[0039] Next, the server uses anonymization techniques to de-identify the identified personal attribute information. This process transforms the personal data into generalized attribute information such as "male in his 20s" or "casual clothing."

[0040] The server then extracts the latest trend information from internet sources, such as social media feeds and news sites. This information is analyzed in real time and used to identify important trends and topics.

[0041] Once anonymized attribute information and trend information are gathered, the server integrates them to generate advertisements or informational content optimized for passersby. The generated content is selected based on the passersby's attributes, and specific advertising themes are extracted.

[0042] Ultimately, the terminal receives content transmitted from the server and displays it on the digital signage. As a result, passersby can see advertisements and information tailored to their interests and needs in real time.

[0043] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose a terminal analyzes attributes such as "a woman in her 30s wearing sportswear," and the server determines that "fitness and health products" are attracting attention as a recent trend. In this case, the server generates an advertisement containing "sale information on the latest fitness wear" based on these attributes and trend information, and the terminal displays it on digital signage. The user can then see this information and instantly obtain highly relevant products and sales information.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The terminal uses the installed camera to capture video information of passersby. This information is acquired as a series of frames and is ready for processing in real time.

[0047] Step 2:

[0048] The server receives video data transmitted from the terminal. To analyze the received data, it performs image analysis using computer vision technology to identify attributes such as the age, gender, facial expression, clothing, and belongings of passersby.

[0049] Step 3:

[0050] The server processes the identified personal attributes using anonymization methods. Specifically, any information that could identify an individual is removed and converted into abstract data such as "male in his 20s" or "business casual attire."

[0051] Step 4:

[0052] The server accesses information sources on the internet and collects the latest trend information using trend information extraction methods. This is a process of collecting data from social media and news sites via APIs and extracting important trends from it.

[0053] Step 5:

[0054] The server integrates anonymized personal attribute information with extracted trend information and generates advertisements or information using content generation methods. The generated content is tailored to the individual's attributes, and specific content such as "Fitness Product Sale" is created.

[0055] Step 6:

[0056] The device receives generated content sent from the server. This content is output to a display device such as a screen and shown to passersby in real time. Users can view the displayed information and receive advertisements and information relevant to them.

[0057] (Example 1)

[0058] 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."

[0059] Modern advertising systems require the real-time delivery of information and advertisements tailored to the interests and needs of passersby. However, providing individually optimized content while maintaining privacy and avoiding personal identification is challenging. Furthermore, rapidly incorporating the latest trends is necessary to enhance advertising effectiveness, but utilizing such dynamic information is technically difficult. Therefore, building systems that provide personalized advertising and information while protecting privacy is a crucial challenge.

[0060] 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.

[0061] In this invention, the server includes data analysis means for acquiring image data of passersby and determining their personal attributes; data anonymization means for de-specificating the determined attribute information and converting it into a format that makes personal identification impossible; and information extraction means for acquiring trend information collected from information sources and identifying important topics. This makes it possible to provide advertisements and information tailored to the interests and needs of passersby in real time while protecting their privacy.

[0062] "Acquiring image data of passersby" means collecting video information of passersby in real time using imaging devices installed on streets and in commercial facilities.

[0063] "Identifying individual attributes" means analyzing received image data and identifying information such as age, gender, and clothing to determine individual characteristics.

[0064] "Data anonymization" is the process of converting identified individual attribute information into a format that does not identify a specific individual.

[0065] "Acquiring trend information collected from information sources" means seeking the latest topics and trends as data in real time from various information platforms on the internet.

[0066] "Identifying important topics" means identifying themes and topics that are currently attracting attention from the collected trending information.

[0067] "Generating personalized information" means creating contextually relevant advertisements and informational content based on anonymized personal attribute information and trend information.

[0068] "Outputting to a video display device" means transmitting generated advertisements or information to a device such as a display.

[0069] This invention is a system aimed at providing personalized advertisements and information to passersby in real time. The system uses advanced digital signage devices installed on streets and in commercial facilities to display advertisements that reflect the interests and needs of passersby.

[0070] The terminal uses high-resolution cameras installed in commercial facilities and public spaces to acquire image data of passersby. The acquired image data is transmitted to a server via a secure network, where data analysis is performed. In the data analysis, image analysis technologies (specifically, software libraries such as OpenCV and TENSORFLOW®) are used to identify characteristics of passersby, such as their age, gender, clothing, facial expression, and belongings.

[0071] The server processes the analyzed personal attribute information using anonymization techniques (e.g., k-anonymization) to transform it into a format that makes it impossible to identify individuals while protecting privacy. The server also utilizes current events information and social media data collected from the internet to obtain the latest trend information. Natural language processing techniques (e.g., NLTK and spaCy) can be used in this process.

[0072] By integrating this information, the server uses a generative AI model (specifically, GPT-4®) to generate personalized advertising content optimized for passersby. The generated content is sent to the terminal and displayed on digital signage. As a result, passersby can see information tailored to their interests and needs in real time, leading to a higher level of satisfaction.

[0073] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose the terminal analyzes attributes such as "a woman in her 30s wearing casual clothing," and the server identifies "eco-friendly products" as a current trend. In this case, the server can generate an advertisement containing "sale information on the latest eco-bags," which the terminal can then display on digital signage.

[0074] Examples of prompts to input into a generative AI model:

[0075] "Please create an advertisement targeting casually dressed women in their 30s, incorporating the latest trends in eco-friendly products."

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The terminal acquires real-time image data of passersby using cameras installed on streets and in commercial facilities. This input image data must be high resolution, clearly showing details such as the faces and postures of passersby. This prepares the system for accurate image analysis in the next step.

[0079] Step 2:

[0080] The device transmits the acquired image data to the server via SSL / TLS encrypted communication. A secure communication protocol is used during this transmission process to ensure data confidentiality. As a result, anonymity is ensured, and personally identifiable information is protected until it reaches the server.

[0081] Step 3:

[0082] The server analyzes the received image data using OpenCV and TensorFlow. By running image processing algorithms on the input images, it identifies personal attributes such as the age, gender, clothing, and facial expressions of passersby. The output is this attribute information.

[0083] Step 4:

[0084] The server de-identifies identified personal attribute information using k-anonymization technology. This process generalizes individual attribute data into categories such as "male in his 20s" or "casual clothing." The output is attribute data in a format that does not identify individuals.

[0085] Step 5:

[0086] The server collects the latest trending information from internet sources. Input data includes Google® News and social media feeds. Natural language processing technologies (such as NLTK and spaCy) are used to analyze this data and extract noteworthy trends. The output is trend information reflecting current popular themes.

[0087] Step 6:

[0088] The server integrates anonymized personal attribute information and trend information, and uses a generative AI model (such as GPT-4) to generate personalized advertising content. This prompt-based generation outputs optimized ads that take attribute information and trends into account.

[0089] Step 7:

[0090] The terminal receives the generated advertising content and displays it on the digital signage. This allows passersby to see information tailored to their interests and needs in real time. The output is the displayed advertisements and information.

[0091] (Application Example 1)

[0092] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0093] There is a need for systems that display advertisements and information optimized for passersby in real time on streets and in commercial facilities. However, providing advertisements that match the interests and needs of passersby without identifying their personal information is not easy. Furthermore, in order to display advertisements efficiently, a method is needed to deliver information directly to the passersby's perspective. Since conventional technologies have difficulty providing such personalized information, the development of more effective methods is desired.

[0094] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0095] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to overlay advertisements onto the user's field of view.

[0096] "Image analysis means" refers to a processing device for determining an individual's age, gender, facial expression, clothing, and belongings from video information of passersby.

[0097] An "anonymization method" is a technology that protects privacy by converting identified individual attribute information into a form that makes it impossible to identify the individual.

[0098] A "trend information extraction method" is a mechanism for collecting, analyzing, and extracting the latest trend information from various sources.

[0099] A "content generation method" is a device that generates appropriate advertisements and information for passersby based on anonymized personal attribute information and trend information.

[0100] "Display control means" refers to a control unit that outputs the generated advertisement or information to a visual device for passersby to see.

[0101] The "glasses-type display device control means" is a mechanism that controls a glasses-type device in order to overlay advertisements onto the user's field of vision.

[0102] The system implementing this invention is comprised of a combination of multiple technological elements to provide passersby with optimized advertisements and information in real time.

[0103] First, the terminal is equipped with a camera, which is used to acquire video information of passersby. This video information includes data such as the individual's age, gender, facial expression, clothing, and belongings. Next, the server receives the video information sent from the terminal and processes this data using image analysis tools. Specifically, it applies technologies such as facial recognition and object detection to extract the necessary personal attribute information. General deep learning libraries can be used for this process.

[0104] The acquired attribute information must be anonymized. The server uses anonymization methods to transform the data into a format that does not identify individuals. This process protects the privacy of passersby.

[0105] Furthermore, the server obtains the latest trend information from various sources via the internet. By using trend information extraction methods, it collects noteworthy topics and trends from social media and news sites. This process can also be analyzed using natural language processing technology.

[0106] Once anonymized personal attribute information and trend information are gathered, the server integrates them and generates advertisements and information using a generative AI model. The generated content is output to the visual device by a glasses-type display device control means so that the advertisement is overlaid on the user's field of view.

[0107] As a concrete example, when a user is walking through a commercial facility, promotional information and the latest product information from nearby stores are displayed on the smart glasses' screen. At this time, the information seen by the user is presented so naturally that it is as if digital signage is superimposed on the real-world scenery.

[0108] An example of a prompt when using a generative AI model is: "Generate the optimal advertising strategy to provide users who are running with real-time information on the latest sales at nearby sporting goods stores."

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The device uses a camera to acquire video information of passersby. The input data is raw video information acquired by the camera, and the output is image data. This image data is used to identify the age, gender, facial expression, clothing, and belongings of passersby.

[0112] Step 2:

[0113] The server receives image data sent from the terminal. The input data is image data sent from the terminal, and the output is attribute information of the identified individual. Using image analysis tools and deep learning technology, the server performs the operation of identifying the personal attributes of passersby.

[0114] Step 3:

[0115] The server anonymizes the identified individual's attribute information using anonymization methods. The input data is the individual's attribute information, and the output is anonymized attribute information. In this step, an anonymization algorithm is used to protect personal information.

[0116] Step 4:

[0117] The server collects the latest trend information from sources via the internet. Input data consists of internet data feeds (social media, news sites, etc.), and output is the collected trend information. It uses trend information extraction methods and natural language processing techniques to analyze important trends.

[0118] Step 5:

[0119] The server uses a generative AI model to generate advertisements and information based on anonymized personal attribute information and trend information. The input data is anonymized personal attribute information and trend information, and the output is generated advertisement content. By inputting prompts into the generative AI model, it generates advertisements appropriate to the user.

[0120] Step 6:

[0121] The terminal receives advertising content transmitted from the server and displays the information in the user's field of view using glasses-type display device control means. The input data is the generated advertising content, and the output is the information displayed on the visual device. The display device is controlled to overlay the information in a natural manner onto the user's field of view.

[0122] 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.

[0123] This invention is a system for displaying optimized advertisements and information to passersby in real time, and further personalizes them by incorporating an emotion engine that analyzes user emotions. Each component works together to provide highly optimized content while protecting individual privacy.

[0124] First, the terminal acquires video information of passersby via a camera installed on it. The data obtained at this stage includes visual information such as the passersby's faces and clothing. The video information is transmitted to the server in real time and processed.

[0125] The server first uses an image analysis algorithm on the transmitted video data. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. It also uses an emotion engine to analyze emotions from the passersby's facial expressions. For example, it analyzes facial features to identify emotions such as "joy" or "surprise."

[0126] The acquired personal attribute information is anonymized using anonymization technology. In this process, personally identifiable information is removed and generalized, such as "a woman in her 30s with a surprised expression."

[0127] The server then collects trend information through internet-based information sources and processes this information using a trend information extraction mechanism. This mechanism uses an API to retrieve the latest trend data and extracts highly relevant information from it.

[0128] Next, anonymized attribute information, analyzed sentiment data, and trend information are integrated to generate content. Specifically, advertising themes and information that take user emotions into account are incorporated. For example, if sentiment analysis identifies a passerby as excited, an advertisement for an energetic music festival will be displayed.

[0129] Finally, the device displays the generated content on its screen. Users can see this personalized information and instantly learn about products and events relevant to them.

[0130] As a concrete example, consider a scenario where the system operates in a commercial facility. If a terminal acquires information that the user is a "man in his 40s who is smiling," and the server grasps the "trend of new gadget products," the emotion engine identifies that the user is in a positive emotional state. In this case, the server generates an advertisement for a "launch event of the latest gadgets" that is appropriate for these attributes and emotions, and the terminal displays it on its screen along with rich images. The user is intrigued by the information and can obtain more detailed information through the display.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The terminal uses the installed camera to capture video information of passersby. This video information is recorded as a series of frames and sent to the server in a state ready for immediate processing.

[0134] Step 2:

[0135] The server performs image analysis on the received video information. Specifically, it uses a machine learning model to detect attributes such as the age, gender, clothing, and belongings of passersby.

[0136] Step 3:

[0137] The server runs an emotion engine in parallel with image analysis, identifying emotions by analyzing the facial expressions of passersby. For example, it can identify emotions such as "joy" from the degree of a smile.

[0138] Step 4:

[0139] The server anonymizes the acquired personal attribute and sentiment data. Here, information that could directly identify an individual is removed, and the data is converted into generalized data such as "a man in his 40s who is smiling."

[0140] Step 5:

[0141] The server connects to internet information sources and collects trend information. Trend information extraction methods are used to identify current trends and user interests.

[0142] Step 6:

[0143] The server integrates anonymized personal attribute information, sentiment data, and trend information, and generates advertisements or information using content generation methods. This content will also take into account the emotional state of passersby.

[0144] Step 7:

[0145] The device displays generated content received from the server on its screen. Users can view the display and receive information that aligns with their emotions and interests, and take action to obtain more detailed information as needed.

[0146] (Example 2)

[0147] 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".

[0148] Making the information and advertisements displayed to passersby more personalized and optimized in real time is a crucial challenge in providing effective information in commercial facilities and public spaces. However, building a system that efficiently presents information without infringing on privacy when handling personal information has not been easy.

[0149] 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.

[0150] In this invention, the server includes an analysis means for acquiring visual information of passersby and determining their personal attributes, a processing means for de-identifying the determined personal information, and an information extraction means for extracting trend information collected from information sources. This makes it possible to provide optimal information based on the user's emotions and tendencies while protecting privacy.

[0151] "Visual information" is a general term for data acquired visually, such as the faces, clothing, and facial expressions of passersby.

[0152] "Analysis means" refers to technologies and devices used to determine the attributes of passersby from acquired visual information.

[0153] "De-identification" is the process of transforming data into a format that makes it impossible to identify individuals.

[0154] "Processing means" refers to technologies or devices used to de-specify the results of the classification.

[0155] "Trend information" refers to data that shows the latest changes and trends in a specific theme or market.

[0156] "Information extraction means" refers to technologies and devices used to collect trend information from information sources and extract necessary elements.

[0157] "Generation means" refers to technologies and devices for creating relevant content based on anonymized attribute information and trend information.

[0158] "Control means" refers to technologies and devices that are responsible for displaying the generated content on an output device.

[0159] A "generative AI model" is a set of algorithms and datasets used to dynamically generate content using machine learning.

[0160] The system of this invention is primarily intended to provide optimized advertisements and information to passersby in real time, mainly in commercial facilities and public spaces. The entire system consists of three main elements: terminals, servers, and users.

[0161] The terminal first uses a high-resolution camera to acquire visual information about passersby. Hardware used includes digital cameras and video acquisition devices, and the video data is captured in a format that allows for real-time processing.

[0162] The server then uses image analysis libraries such as OpenCV and TensorFlow to determine the age, gender, clothing, facial expression, and belongings of passersby from the video information. Furthermore, an emotion engine analyzes the facial expressions to identify the user's emotions. The analysis results are then anonymized to a format that does not allow for the identification of individuals. Appropriate consideration is given to respecting individual privacy during this process.

[0163] The server is also responsible for collecting trend information from the internet. APIs are used for information extraction, including current events and data from online platforms. This information is kept constantly up-to-date.

[0164] The generative AI model combines anonymized personal attribute information, analyzed sentiment data, and trend information to generate personalized advertisements and informational content. This algorithm allows, for example, to prioritize providing information on relevant music or sporting events if a user is excited.

[0165] A concrete example is when a device acquires information such as "a man in his 40s who is smiling." In this case, the server grasps the "trend of new gadget products," and the generative AI model generates information about "launch events for the latest gadgets." The device displays this information on its screen, and the user can obtain further details from the display.

[0166] An example of a prompt message would be: "Generate an ad for a smiling man in his 40s, taking into account the latest gadget trends."

[0167] Therefore, this system can maximize the effectiveness of information provision in facilities and stores by providing valuable information to users and attracting their interest.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The device uses a high-resolution camera to acquire visual information about passersby. The input is real-time video data including the passersby's faces, clothing, and facial expressions. This data is pre-processed so that it can be instantly transmitted to the server.

[0171] Step 2:

[0172] The server processes the received video data through an image analysis algorithm. The input is raw video data sent from the terminal, and the output is the identification results of the age, gender, clothing, facial expression, and belongings of passersby. Here, an image recognition library is used to perform face recognition and object classification to identify each attribute.

[0173] Step 3:

[0174] The server anonymizes the analyzed personal attribute information. The input is already identified attribute information, and the output is anonymized data from which the ability to identify an individual has been removed. For example, it is converted into a generalized format such as "a woman in her 30s, wearing casual clothes."

[0175] Step 4:

[0176] The server collects trend information using an internet API. The input is unorganized data from multiple sources, and the output is the latest extracted trend information. At this stage, text analysis is performed to efficiently process the trend information.

[0177] Step 5:

[0178] The content generation method utilizes a generative AI model to integrate anonymized attribute information, analyzed sentiment data, and trend information. The input is a combination of these data, and the output is advertisements and informational content that reflect the user's emotions and preferences. For example, if the user is identified as smiling, a friendly product promotion will be created.

[0179] Step 6:

[0180] The terminal displays the generated content on its screen. The input is pre-generated content sent from the server, and the output is visual information displayed to the user. Specifically, presentations are given using vivid images and videos, and the user can receive information directly from the display.

[0181] (Application Example 2)

[0182] 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".

[0183] Modern advertising and information display systems are insufficiently personalized based on the emotions and attributes of individual passersby. Furthermore, there is a need for means of directly displaying information tailored to the individual through personal devices, particularly smart glasses. This invention aims to provide real-time optimized advertising within the user's visual field, based on their individual emotional state and trend information.

[0184] 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.

[0185] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to display surrounding information in the passerby's field of vision in real time via a visual interface.

[0186] "Video information of passersby" refers to visual data recorded by cameras or other devices showing people passing through a specific location.

[0187] "Image analysis means" refers to technology used to identify individual attributes such as age, gender, facial expression, clothing, and possessions from video information.

[0188] An "anonymization method" is a process for converting acquired personal information into a format in which the individual cannot be identified.

[0189] A "trend information extraction method" is a technology that collects and analyzes the latest trend information from information sources such as the internet.

[0190] "Content generation methods" refer to technologies that create optimal advertisements and information based on anonymized personal attribute information and trend information.

[0191] "Display control means" refers to control technology for outputting generated advertisements and information to a designated display.

[0192] "Visual output means" refers to technologies that display information directly in the user's field of vision through devices such as smart glasses.

[0193] This invention is a system that displays optimized advertisements based on specific attribute information and emotional states of passersby. It consists of three roles: server, terminal, and user.

[0194] The server acquires video information of passersby from cameras built into smart glasses or similar devices. Using image analysis technologies such as OpenCV and TensorFlow, it identifies the age, gender, facial expression, clothing, and belongings of passersby and anonymizes this information. Based on the anonymized information, it collects current events and trend data from information sources via APIs in order to extract trend information. Based on this information, it uses content generation tools to generate advertisements and information optimized for the attributes and emotions of passersby.

[0195] The device is a smart glasses or other device worn by the user, which displays content received from a server in real time within the user's field of vision through visual output means. This allows the user to intuitively obtain the information and advertisements most relevant to them.

[0196] As a concrete example, consider a male user in his 40s walking through a town where a new cafe has opened. If this user smiles, the camera recognizes his emotional state, and the server identifies the new cafe's opening information. It then generates an appropriate advertisement and displays an offer of "free new cappuccino" on the user's smart glasses. In this way, users can instantly obtain local information and become interested in it.

[0197] An example of a prompt sentence to input into a generative AI model is, "What kind of advertisement would be appropriate to display in the street when a man in his 40s is smiling?"

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The device acquires real-time video information of passersby using its built-in camera. The image data captured by the camera is used as input.

[0201] Step 2:

[0202] The server receives video information transmitted from the terminal and performs image analysis using OpenCV. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. The identified attribute information is then output.

[0203] Step 3:

[0204] The server analyzes emotions from facial expressions identified using TensorFlow. Facial expression data is used as input, and emotional information such as joy or surprise is output through the analysis.

[0205] Step 4:

[0206] The server converts the identified attribute and sentiment information into a format that does not identify individuals using anonymization methods. Attribute and sentiment information are used as input, and anonymized data is output.

[0207] Step 5:

[0208] The server collects the latest trend information from the internet via an API. The acquired data is processed by a trend information extraction method, and highly relevant trend information is output.

[0209] Step 6:

[0210] The server receives anonymized attribute information, sentiment information, and trend information as input, and generates optimized advertising content using content generation methods. The generated advertising content is then output.

[0211] Step 7:

[0212] The device receives advertising content transmitted from the server and displays it within the user's field of view using visual output means. Information optimized for the user is delivered specifically.

[0213] Step 8:

[0214] Users review the advertising content displayed on their device and take actions to obtain more detailed information as needed. This allows them to instantly grasp information that interests them.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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".

[0231] This invention is a digital signage system for displaying optimized advertisements and information to passersby in real time. Each element works in conjunction to enable the generation and display of personalized content while avoiding the identification of personal information.

[0232] First, the terminal uses cameras installed on streets and in commercial facilities to acquire video information of passersby. This video information is transmitted to the server in real time. After receiving this video information, the server uses image analysis technology to identify personal attributes of passersby, such as age, gender, facial expression, clothing, and belongings.

[0233] Next, the server uses anonymization techniques to de-identify the identified personal attribute information. This process transforms the personal data into generalized attribute information such as "male in his 20s" or "casual clothing."

[0234] The server then extracts the latest trend information from internet sources, such as social media feeds and news sites. This information is analyzed in real time and used to identify important trends and topics.

[0235] Once anonymized attribute information and trend information are gathered, the server integrates them to generate advertisements or informational content optimized for passersby. The generated content is selected based on the passersby's attributes, and specific advertising themes are extracted.

[0236] Ultimately, the terminal receives content transmitted from the server and displays it on the digital signage. As a result, passersby can see advertisements and information tailored to their interests and needs in real time.

[0237] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose a terminal analyzes attributes such as "a woman in her 30s wearing sportswear," and the server determines that "fitness and health products" are attracting attention as a recent trend. In this case, the server generates an advertisement containing "sale information on the latest fitness wear" based on these attributes and trend information, and the terminal displays it on digital signage. The user can then see this information and instantly obtain highly relevant products and sales information.

[0238] The following describes the processing flow.

[0239] Step 1:

[0240] The terminal uses the installed camera to capture video information of passersby. This information is acquired as a series of frames and is ready for processing in real time.

[0241] Step 2:

[0242] The server receives video data transmitted from the terminal. To analyze the received data, it performs image analysis using computer vision technology to identify attributes such as the age, gender, facial expression, clothing, and belongings of passersby.

[0243] Step 3:

[0244] The server processes the identified personal attributes using anonymization methods. Specifically, any information that could identify an individual is removed and converted into abstract data such as "male in his 20s" or "business casual attire."

[0245] Step 4:

[0246] The server accesses information sources on the internet and collects the latest trend information using trend information extraction methods. This is a process of collecting data from social media and news sites via APIs and extracting important trends from it.

[0247] Step 5:

[0248] The server integrates anonymized personal attribute information with extracted trend information and generates advertisements or information using content generation methods. The generated content is tailored to the individual's attributes, and specific content such as "Fitness Product Sale" is created.

[0249] Step 6:

[0250] The device receives generated content sent from the server. This content is output to a display device such as a screen and shown to passersby in real time. Users can view the displayed information and receive advertisements and information relevant to them.

[0251] (Example 1)

[0252] 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."

[0253] Modern advertising systems require the real-time delivery of information and advertisements tailored to the interests and needs of passersby. However, providing individually optimized content while maintaining privacy and avoiding personal identification is challenging. Furthermore, rapidly incorporating the latest trends is necessary to enhance advertising effectiveness, but utilizing such dynamic information is technically difficult. Therefore, building systems that provide personalized advertising and information while protecting privacy is a crucial challenge.

[0254] 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.

[0255] In this invention, the server includes data analysis means for acquiring image data of passersby and determining their personal attributes; data anonymization means for de-specificating the determined attribute information and converting it into a format that makes personal identification impossible; and information extraction means for acquiring trend information collected from information sources and identifying important topics. This makes it possible to provide advertisements and information tailored to the interests and needs of passersby in real time while protecting their privacy.

[0256] "Acquiring image data of passersby" means collecting video information of passersby in real time using imaging devices installed on streets and in commercial facilities.

[0257] "Identifying individual attributes" means analyzing received image data and identifying information such as age, gender, and clothing to determine individual characteristics.

[0258] "Data anonymization" is the process of converting identified individual attribute information into a format that does not identify a specific individual.

[0259] "Acquiring trend information collected from information sources" means seeking the latest topics and trends as data in real time from various information platforms on the internet.

[0260] "Identifying important topics" means identifying themes and topics that are currently attracting attention from the collected trending information.

[0261] "Generating personalized information" means creating contextually relevant advertisements and informational content based on anonymized personal attribute information and trend information.

[0262] "Outputting to a video display device" means transmitting generated advertisements or information to a device such as a display.

[0263] This invention is a system aimed at providing personalized advertisements and information to passersby in real time. The system uses advanced digital signage devices installed on streets and in commercial facilities to display advertisements that reflect the interests and needs of passersby.

[0264] The terminal uses high-resolution cameras installed in commercial facilities and public spaces to acquire image data of passersby. The acquired image data is transmitted to a server via a secure network, where data analysis is performed. In the data analysis, image analysis techniques (specifically, software libraries such as OpenCV and TensorFlow) are used to identify characteristics of passersby such as age, gender, clothing, facial expression, and belongings.

[0265] The server processes the analyzed personal attribute information using anonymization techniques (e.g., k-anonymization) to transform it into a format that makes it impossible to identify individuals while protecting privacy. The server also utilizes current events information and social media data collected from the internet to obtain the latest trend information. Natural language processing techniques (e.g., NLTK and spaCy) can be used in this process.

[0266] By integrating this information, the server uses a generative AI model (GPT-4, for example) to generate personalized advertising content optimized for passersby. The generated content is sent to the device and displayed on digital signage. As a result, passersby can see information tailored to their interests and needs in real time, leading to a higher level of satisfaction.

[0267] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose the terminal analyzes attributes such as "a woman in her 30s wearing casual clothing," and the server identifies "eco-friendly products" as a current trend. In this case, the server can generate an advertisement containing "sale information on the latest eco-bags," which the terminal can then display on digital signage.

[0268] Examples of prompts to input into a generative AI model:

[0269] "Please create an advertisement targeting casually dressed women in their 30s, incorporating the latest trends in eco-friendly products."

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The terminal acquires real-time image data of passersby using cameras installed on streets and in commercial facilities. This input image data must be high resolution, clearly showing details such as the faces and postures of passersby. This prepares the system for accurate image analysis in the next step.

[0273] Step 2:

[0274] The device transmits the acquired image data to the server via SSL / TLS encrypted communication. A secure communication protocol is used during this transmission process to ensure data confidentiality. As a result, anonymity is ensured, and personally identifiable information is protected until it reaches the server.

[0275] Step 3:

[0276] The server analyzes the received image data using OpenCV and TensorFlow. By running image processing algorithms on the input images, it identifies personal attributes such as the age, gender, clothing, and facial expressions of passersby. The output is this attribute information.

[0277] Step 4:

[0278] The server de-identifies identified personal attribute information using k-anonymization technology. This process generalizes individual attribute data into categories such as "male in his 20s" or "casual clothing." The output is attribute data in a format that does not identify individuals.

[0279] Step 5:

[0280] The server collects the latest trending information from internet sources. Input data includes Google News and social media feeds, which are analyzed using natural language processing technologies (such as NLTK and spaCy) to extract noteworthy trends. The output is trend information reflecting current popular themes.

[0281] Step 6:

[0282] The server integrates the anonymized personal attribute information and popularity information, and uses a generative AI model (such as GPT-4) to generate personalized advertising content. In this generation by the prompt text, optimized advertisements considering the attribute information and trends are output.

[0283] Step 7:

[0284] The terminal receives the generated advertising content and displays it on the digital signage. By this operation, the passerby who is the user can view information that matches their interests and needs in real time. The output is the displayed advertisement or information.

[0285] (Application Example 1)

[0286] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0287] There is a demand for a system that displays optimized advertisements and information for passersby in real time on the streets and commercial facilities. However, it is not easy to provide advertisements according to the interests and needs of passersby without identifying personal information. Also, in order to display advertisements efficiently, a method of directly providing information from the perspective of the passerby is required. In the conventional technology, it is difficult to provide such personalized information, so the development of a more effective method is desired.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0289] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to overlay advertisements onto the user's field of view.

[0290] "Image analysis means" refers to a processing device for determining an individual's age, gender, facial expression, clothing, and belongings from video information of passersby.

[0291] An "anonymization method" is a technology that protects privacy by converting identified individual attribute information into a form that makes it impossible to identify the individual.

[0292] A "trend information extraction method" is a mechanism for collecting, analyzing, and extracting the latest trend information from various sources.

[0293] A "content generation method" is a device that generates appropriate advertisements and information for passersby based on anonymized personal attribute information and trend information.

[0294] "Display control means" refers to a control unit that outputs the generated advertisement or information to a visual device for passersby to see.

[0295] The "glasses-type display device control means" is a mechanism that controls a glasses-type device in order to overlay advertisements onto the user's field of vision.

[0296] The system implementing this invention is comprised of a combination of multiple technological elements to provide passersby with optimized advertisements and information in real time.

[0297] First, the terminal is equipped with a camera, which is used to acquire video information of passersby. This video information includes data such as the individual's age, gender, facial expression, clothing, and belongings. Next, the server receives the video information sent from the terminal and processes this data using image analysis tools. Specifically, it applies technologies such as facial recognition and object detection to extract the necessary personal attribute information. General deep learning libraries can be used for this process.

[0298] The acquired attribute information must be anonymized. The server uses anonymization methods to transform the data into a format that does not identify individuals. This process protects the privacy of passersby.

[0299] Furthermore, the server obtains the latest trend information from various sources via the internet. By using trend information extraction methods, it collects noteworthy topics and trends from social media and news sites. This process can also be analyzed using natural language processing technology.

[0300] Once anonymized personal attribute information and trend information are gathered, the server integrates them and generates advertisements and information using a generative AI model. The generated content is output to the visual device by a glasses-type display device control means so that the advertisement is overlaid on the user's field of view.

[0301] As a concrete example, when a user is walking through a commercial facility, promotional information and the latest product information from nearby stores are displayed on the smart glasses' screen. At this time, the information seen by the user is presented so naturally that it is as if digital signage is superimposed on the real-world scenery.

[0302] An example of a prompt when using a generative AI model is: "Generate the optimal advertising strategy to provide users who are running with real-time information on the latest sales at nearby sporting goods stores."

[0303] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0304] Step 1:

[0305] The terminal acquires video information of the passerby using a camera. The input data is the raw video information acquired by the camera, and the output is image data. This image data is used to determine the age, gender, expression, clothing, and belongings of the passerby.

[0306] Step 2:

[0307] The server receives the image data sent from the terminal. The input data is the image data transmitted from the terminal, and the output is the determined personal attribute information. Using image analysis means, an operation is performed to utilize deep learning technology to identify the personal attributes of the passerby.

[0308] Step 3:

[0309] The server anonymizes the determined personal attribute information using anonymization means. The input data is the personal attribute information, and the output is the anonymized attribute information. In this step, an operation is performed to protect personal information using an anonymization algorithm.

[0310] Step 4:

[0311] The server collects the latest trend information from information sources through the Internet. The input data is data feeds on the Internet (such as social media, news sites, etc.), and the output is the collected trend information. Using trend information extraction means, an operation is performed to analyze important trends using natural language processing technology.

[0312] Step 5:

[0313] The server uses a generative AI model to generate advertisements and information based on anonymized personal attribute information and trend information. The input data is anonymized personal attribute information and trend information, and the output is generated advertisement content. By inputting prompts into the generative AI model, it generates advertisements appropriate to the user.

[0314] Step 6:

[0315] The terminal receives advertising content transmitted from the server and displays the information in the user's field of view using glasses-type display device control means. The input data is the generated advertising content, and the output is the information displayed on the visual device. The display device is controlled to overlay the information in a natural manner onto the user's field of view.

[0316] 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.

[0317] This invention is a system for displaying optimized advertisements and information to passersby in real time, and further personalizes them by incorporating an emotion engine that analyzes user emotions. Each component works together to provide highly optimized content while protecting individual privacy.

[0318] First, the terminal acquires video information of passersby via a camera installed on it. The data obtained at this stage includes visual information such as the passersby's faces and clothing. The video information is transmitted to the server in real time and processed.

[0319] The server first uses an image analysis algorithm on the transmitted video data. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. It also uses an emotion engine to analyze emotions from the passersby's facial expressions. For example, it analyzes facial features to identify emotions such as "joy" or "surprise."

[0320] The acquired personal attribute information is anonymized using anonymization technology. In this process, personally identifiable information is removed and generalized, such as "a woman in her 30s with a surprised expression."

[0321] The server then collects trend information through internet-based information sources and processes this information using a trend information extraction mechanism. This mechanism uses an API to retrieve the latest trend data and extracts highly relevant information from it.

[0322] Next, anonymized attribute information, analyzed sentiment data, and trend information are integrated to generate content. Specifically, advertising themes and information that take user emotions into account are incorporated. For example, if sentiment analysis identifies a passerby as excited, an advertisement for an energetic music festival will be displayed.

[0323] Finally, the device displays the generated content on its screen. Users can see this personalized information and instantly learn about products and events relevant to them.

[0324] As a concrete example, consider a scenario where the system operates in a commercial facility. If a terminal acquires information that the user is a "man in his 40s who is smiling," and the server grasps the "trend of new gadget products," the emotion engine identifies that the user is in a positive emotional state. In this case, the server generates an advertisement for a "launch event of the latest gadgets" that is appropriate for these attributes and emotions, and the terminal displays it on its screen along with rich images. The user is intrigued by the information and can obtain more detailed information through the display.

[0325] The following describes the processing flow.

[0326] Step 1:

[0327] The terminal uses the installed camera to capture video information of passersby. This video information is recorded as a series of frames and sent to the server in a state ready for immediate processing.

[0328] Step 2:

[0329] The server performs image analysis on the received video information. Specifically, it uses a machine learning model to detect attributes such as the age, gender, clothing, and belongings of passersby.

[0330] Step 3:

[0331] The server runs an emotion engine in parallel with image analysis, identifying emotions by analyzing the facial expressions of passersby. For example, it can identify emotions such as "joy" from the degree of a smile.

[0332] Step 4:

[0333] The server anonymizes the acquired personal attribute and sentiment data. Here, information that could directly identify an individual is removed, and the data is converted into generalized data such as "a man in his 40s who is smiling."

[0334] Step 5:

[0335] The server connects to internet information sources and collects trend information. Trend information extraction methods are used to identify current trends and user interests.

[0336] Step 6:

[0337] The server integrates anonymized personal attribute information, sentiment data, and trend information, and generates advertisements or information using content generation methods. This content will also take into account the emotional state of passersby.

[0338] Step 7:

[0339] The device displays generated content received from the server on its screen. Users can view the display and receive information that aligns with their emotions and interests, and take action to obtain more detailed information as needed.

[0340] (Example 2)

[0341] 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".

[0342] Making the information and advertisements displayed to passersby more personalized and optimized in real time is a crucial challenge in providing effective information in commercial facilities and public spaces. However, building a system that efficiently presents information without infringing on privacy when handling personal information has not been easy.

[0343] 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.

[0344] In this invention, the server includes an analysis means for acquiring visual information of passersby and determining their personal attributes, a processing means for de-identifying the determined personal information, and an information extraction means for extracting trend information collected from information sources. This makes it possible to provide optimal information based on the user's emotions and tendencies while protecting privacy.

[0345] "Visual information" is a general term for data acquired visually, such as the faces, clothing, and facial expressions of passersby.

[0346] "Analysis means" refers to technologies and devices used to determine the attributes of passersby from acquired visual information.

[0347] "De-identification" is the process of transforming data into a format that makes it impossible to identify individuals.

[0348] "Processing means" refers to technologies or devices used to de-specify the results of the classification.

[0349] "Trend information" refers to data that shows the latest changes and trends in a specific theme or market.

[0350] "Information extraction means" refers to technologies and devices used to collect trend information from information sources and extract necessary elements.

[0351] "Generation means" refers to technologies and devices for creating relevant content based on anonymized attribute information and trend information.

[0352] "Control means" refers to technologies and devices that are responsible for displaying the generated content on an output device.

[0353] A "generative AI model" is a set of algorithms and datasets used to dynamically generate content using machine learning.

[0354] The system of this invention is primarily intended to provide optimized advertisements and information to passersby in real time, mainly in commercial facilities and public spaces. The entire system consists of three main elements: terminals, servers, and users.

[0355] The terminal first uses a high-resolution camera to acquire visual information about passersby. Hardware used includes digital cameras and video acquisition devices, and the video data is captured in a format that allows for real-time processing.

[0356] The server then uses image analysis libraries such as OpenCV and TensorFlow to determine the age, gender, clothing, facial expression, and belongings of passersby from the video information. Furthermore, an emotion engine analyzes the facial expressions to identify the user's emotions. The analysis results are then anonymized to a format that does not allow for the identification of individuals. Appropriate consideration is given to respecting individual privacy during this process.

[0357] The server is also responsible for collecting trend information from the internet. APIs are used for information extraction, including current events and data from online platforms. This information is kept constantly up-to-date.

[0358] The generative AI model combines anonymized personal attribute information, analyzed sentiment data, and trend information to generate personalized advertisements and informational content. This algorithm allows, for example, to prioritize providing information on relevant music or sporting events if a user is excited.

[0359] A concrete example is when a device acquires information such as "a man in his 40s who is smiling." In this case, the server grasps the "trend of new gadget products," and the generative AI model generates information about "launch events for the latest gadgets." The device displays this information on its screen, and the user can obtain further details from the display.

[0360] An example of a prompt message would be: "Generate an ad for a smiling man in his 40s, taking into account the latest gadget trends."

[0361] Therefore, this system can maximize the effectiveness of information provision in facilities and stores by providing valuable information to users and attracting their interest.

[0362] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0363] Step 1:

[0364] The device uses a high-resolution camera to acquire visual information about passersby. The input is real-time video data including the passersby's faces, clothing, and facial expressions. This data is pre-processed so that it can be instantly transmitted to the server.

[0365] Step 2:

[0366] The server processes the received video data through an image analysis algorithm. The input is raw video data sent from the terminal, and the output is the identification results of the age, gender, clothing, facial expression, and belongings of passersby. Here, an image recognition library is used to perform face recognition and object classification to identify each attribute.

[0367] Step 3:

[0368] The server anonymizes the analyzed personal attribute information. The input is already identified attribute information, and the output is anonymized data from which the ability to identify an individual has been removed. For example, it is converted into a generalized format such as "a woman in her 30s, wearing casual clothes."

[0369] Step 4:

[0370] The server collects trend information using an internet API. The input is unorganized data from multiple sources, and the output is the latest extracted trend information. At this stage, text analysis is performed to efficiently process the trend information.

[0371] Step 5:

[0372] The content generation method utilizes a generative AI model to integrate anonymized attribute information, analyzed sentiment data, and trend information. The input is a combination of these data, and the output is advertisements and informational content that reflect the user's emotions and preferences. For example, if the user is identified as smiling, a friendly product promotion will be created.

[0373] Step 6:

[0374] The terminal displays the generated content on its screen. The input is pre-generated content sent from the server, and the output is visual information displayed to the user. Specifically, presentations are given using vivid images and videos, and the user can receive information directly from the display.

[0375] (Application Example 2)

[0376] 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."

[0377] Modern advertising and information display systems are insufficiently personalized based on the emotions and attributes of individual passersby. Furthermore, there is a need for means of directly displaying information tailored to the individual through personal devices, particularly smart glasses. This invention aims to provide real-time optimized advertising within the user's visual field, based on their individual emotional state and trend information.

[0378] 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.

[0379] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to display surrounding information in the passerby's field of vision in real time via a visual interface.

[0380] "Video information of passersby" refers to visual data recorded by cameras or other devices showing people passing through a specific location.

[0381] "Image analysis means" refers to technology used to identify individual attributes such as age, gender, facial expression, clothing, and possessions from video information.

[0382] An "anonymization method" is a process for converting acquired personal information into a format in which the individual cannot be identified.

[0383] A "trend information extraction method" is a technology that collects and analyzes the latest trend information from information sources such as the internet.

[0384] "Content generation methods" refer to technologies that create optimal advertisements and information based on anonymized personal attribute information and trend information.

[0385] "Display control means" refers to control technology for outputting generated advertisements and information to a designated display.

[0386] "Visual output means" refers to technologies that display information directly in the user's field of vision through devices such as smart glasses.

[0387] This invention is a system that displays optimized advertisements based on specific attribute information and emotional states of passersby. It consists of three roles: server, terminal, and user.

[0388] The server acquires video information of passersby from cameras built into smart glasses or similar devices. Using image analysis technologies such as OpenCV and TensorFlow, it identifies the age, gender, facial expression, clothing, and belongings of passersby and anonymizes this information. Based on the anonymized information, it collects current events and trend data from information sources via APIs in order to extract trend information. Based on this information, it uses content generation tools to generate advertisements and information optimized for the attributes and emotions of passersby.

[0389] The device is a smart glasses or other device worn by the user, which displays content received from a server in real time within the user's field of vision through visual output means. This allows the user to intuitively obtain the information and advertisements most relevant to them.

[0390] As a concrete example, consider a male user in his 40s walking through a town where a new cafe has opened. If this user smiles, the camera recognizes his emotional state, and the server identifies the new cafe's opening information. It then generates an appropriate advertisement and displays an offer of "free new cappuccino" on the user's smart glasses. In this way, users can instantly obtain local information and become interested in it.

[0391] An example of a prompt sentence to input into a generative AI model is, "What kind of advertisement would be appropriate to display in the street when a man in his 40s is smiling?"

[0392] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0393] Step 1:

[0394] The device acquires real-time video information of passersby using its built-in camera. The image data captured by the camera is used as input.

[0395] Step 2:

[0396] The server receives video information transmitted from the terminal and performs image analysis using OpenCV. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. The identified attribute information is then output.

[0397] Step 3:

[0398] The server analyzes emotions from facial expressions identified using TensorFlow. Facial expression data is used as input, and emotional information such as joy or surprise is output through the analysis.

[0399] Step 4:

[0400] The server converts the identified attribute and sentiment information into a format that does not identify individuals using anonymization methods. Attribute and sentiment information are used as input, and anonymized data is output.

[0401] Step 5:

[0402] The server collects the latest trend information from the internet via an API. The acquired data is processed by a trend information extraction method, and highly relevant trend information is output.

[0403] Step 6:

[0404] The server receives anonymized attribute information, sentiment information, and trend information as input, and generates optimized advertising content using content generation methods. The generated advertising content is then output.

[0405] Step 7:

[0406] The device receives advertising content transmitted from the server and displays it within the user's field of view using visual output means. Information optimized for the user is delivered specifically.

[0407] Step 8:

[0408] Users review the advertising content displayed on their device and take actions to obtain more detailed information as needed. This allows them to instantly grasp information that interests them.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] [Third Embodiment]

[0413] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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".

[0425] This invention is a digital signage system for displaying optimized advertisements and information to passersby in real time. Each element works in conjunction to enable the generation and display of personalized content while avoiding the identification of personal information.

[0426] First, the terminal uses cameras installed on streets and in commercial facilities to acquire video information of passersby. This video information is transmitted to the server in real time. After receiving this video information, the server uses image analysis technology to identify personal attributes of passersby, such as age, gender, facial expression, clothing, and belongings.

[0427] Next, the server uses anonymization techniques to de-identify the identified personal attribute information. This process transforms the personal data into generalized attribute information such as "male in his 20s" or "casual clothing."

[0428] The server then extracts the latest trend information from internet sources, such as social media feeds and news sites. This information is analyzed in real time and used to identify important trends and topics.

[0429] Once anonymized attribute information and trend information are gathered, the server integrates them to generate advertisements or informational content optimized for passersby. The generated content is selected based on the passersby's attributes, and specific advertising themes are extracted.

[0430] Ultimately, the terminal receives content transmitted from the server and displays it on the digital signage. As a result, passersby can see advertisements and information tailored to their interests and needs in real time.

[0431] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose a terminal analyzes attributes such as "a woman in her 30s wearing sportswear," and the server determines that "fitness and health products" are attracting attention as a recent trend. In this case, the server generates an advertisement containing "sale information on the latest fitness wear" based on these attributes and trend information, and the terminal displays it on digital signage. The user can then see this information and instantly obtain highly relevant products and sales information.

[0432] The following describes the processing flow.

[0433] Step 1:

[0434] The terminal uses the installed camera to capture video information of passersby. This information is acquired as a series of frames and is ready for processing in real time.

[0435] Step 2:

[0436] The server receives video data transmitted from the terminal. To analyze the received data, it performs image analysis using computer vision technology to identify attributes such as the age, gender, facial expression, clothing, and belongings of passersby.

[0437] Step 3:

[0438] The server processes the identified personal attributes using anonymization methods. Specifically, any information that could identify an individual is removed and converted into abstract data such as "male in his 20s" or "business casual attire."

[0439] Step 4:

[0440] The server accesses information sources on the internet and collects the latest trend information using trend information extraction methods. This is a process of collecting data from social media and news sites via APIs and extracting important trends from it.

[0441] Step 5:

[0442] The server integrates anonymized personal attribute information with extracted trend information and generates advertisements or information using content generation methods. The generated content is tailored to the individual's attributes, and specific content such as "Fitness Product Sale" is created.

[0443] Step 6:

[0444] The device receives generated content sent from the server. This content is output to a display device such as a screen and shown to passersby in real time. Users can view the displayed information and receive advertisements and information relevant to them.

[0445] (Example 1)

[0446] 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."

[0447] Modern advertising systems require the real-time delivery of information and advertisements tailored to the interests and needs of passersby. However, providing individually optimized content while maintaining privacy and avoiding personal identification is challenging. Furthermore, rapidly incorporating the latest trends is necessary to enhance advertising effectiveness, but utilizing such dynamic information is technically difficult. Therefore, building systems that provide personalized advertising and information while protecting privacy is a crucial challenge.

[0448] 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.

[0449] In this invention, the server includes data analysis means for acquiring image data of passersby and determining their personal attributes; data anonymization means for de-specificating the determined attribute information and converting it into a format that makes personal identification impossible; and information extraction means for acquiring trend information collected from information sources and identifying important topics. This makes it possible to provide advertisements and information tailored to the interests and needs of passersby in real time while protecting their privacy.

[0450] "Acquiring image data of passersby" means collecting video information of passersby in real time using imaging devices installed on streets and in commercial facilities.

[0451] "Identifying individual attributes" means analyzing received image data and identifying information such as age, gender, and clothing to determine individual characteristics.

[0452] "Data anonymization" is the process of converting identified individual attribute information into a format that does not identify a specific individual.

[0453] "Acquiring trend information collected from information sources" means seeking the latest topics and trends as data in real time from various information platforms on the internet.

[0454] "Identifying important topics" means identifying themes and topics that are currently attracting attention from the collected trending information.

[0455] "Generating personalized information" means creating contextually relevant advertisements and informational content based on anonymized personal attribute information and trend information.

[0456] "Outputting to a video display device" means transmitting generated advertisements or information to a device such as a display.

[0457] This invention is a system aimed at providing personalized advertisements and information to passersby in real time. The system uses advanced digital signage devices installed on streets and in commercial facilities to display advertisements that reflect the interests and needs of passersby.

[0458] The terminal uses high-resolution cameras installed in commercial facilities and public spaces to acquire image data of passersby. The acquired image data is transmitted to a server via a secure network, where data analysis is performed. In the data analysis, image analysis techniques (specifically, software libraries such as OpenCV and TensorFlow) are used to identify characteristics of passersby such as age, gender, clothing, facial expression, and belongings.

[0459] The server processes the analyzed personal attribute information using anonymization techniques (e.g., k-anonymization) to transform it into a format that makes it impossible to identify individuals while protecting privacy. The server also utilizes current events information and social media data collected from the internet to obtain the latest trend information. Natural language processing techniques (e.g., NLTK and spaCy) can be used in this process.

[0460] By integrating this information, the server uses a generative AI model (GPT-4, for example) to generate personalized advertising content optimized for passersby. The generated content is sent to the device and displayed on digital signage. As a result, passersby can see information tailored to their interests and needs in real time, leading to a higher level of satisfaction.

[0461] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose the terminal analyzes attributes such as "a woman in her 30s wearing casual clothing," and the server identifies "eco-friendly products" as a current trend. In this case, the server can generate an advertisement containing "sale information on the latest eco-bags," which the terminal can then display on digital signage.

[0462] Examples of prompts to input into a generative AI model:

[0463] "Please create an advertisement targeting casually dressed women in their 30s, incorporating the latest trends in eco-friendly products."

[0464] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0465] Step 1:

[0466] The terminal acquires real-time image data of passersby using cameras installed on streets and in commercial facilities. This input image data must be high resolution, clearly showing details such as the faces and postures of passersby. This prepares the system for accurate image analysis in the next step.

[0467] Step 2:

[0468] The device transmits the acquired image data to the server via SSL / TLS encrypted communication. A secure communication protocol is used during this transmission process to ensure data confidentiality. As a result, anonymity is ensured, and personally identifiable information is protected until it reaches the server.

[0469] Step 3:

[0470] The server analyzes the received image data using OpenCV and TensorFlow. By running image processing algorithms on the input images, it identifies personal attributes such as the age, gender, clothing, and facial expressions of passersby. The output is this attribute information.

[0471] Step 4:

[0472] The server de-identifies identified personal attribute information using k-anonymization technology. This process generalizes individual attribute data into categories such as "male in his 20s" or "casual clothing." The output is attribute data in a format that does not identify individuals.

[0473] Step 5:

[0474] The server collects the latest trending information from internet sources. Input data includes Google News and social media feeds, which are analyzed using natural language processing technologies (such as NLTK and spaCy) to extract noteworthy trends. The output is trend information reflecting current popular themes.

[0475] Step 6:

[0476] The server integrates anonymized personal attribute information and trend information, and uses a generative AI model (such as GPT-4) to generate personalized advertising content. This prompt-based generation outputs optimized ads that take attribute information and trends into account.

[0477] Step 7:

[0478] The terminal receives the generated advertising content and displays it on the digital signage. This allows passersby to see information tailored to their interests and needs in real time. The output is the displayed advertisements and information.

[0479] (Application Example 1)

[0480] 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."

[0481] There is a need for systems that display advertisements and information optimized for passersby in real time on streets and in commercial facilities. However, providing advertisements that match the interests and needs of passersby without identifying their personal information is not easy. Furthermore, in order to display advertisements efficiently, a method is needed to deliver information directly to the passersby's perspective. Since conventional technologies have difficulty providing such personalized information, the development of more effective methods is desired.

[0482] 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.

[0483] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to overlay advertisements onto the user's field of view.

[0484] "Image analysis means" refers to a processing device for determining an individual's age, gender, facial expression, clothing, and belongings from video information of passersby.

[0485] An "anonymization method" is a technology that protects privacy by converting identified individual attribute information into a form that makes it impossible to identify the individual.

[0486] A "trend information extraction method" is a mechanism for collecting, analyzing, and extracting the latest trend information from various sources.

[0487] A "content generation method" is a device that generates appropriate advertisements and information for passersby based on anonymized personal attribute information and trend information.

[0488] "Display control means" refers to a control unit that outputs the generated advertisement or information to a visual device for passersby to see.

[0489] The "glasses-type display device control means" is a mechanism that controls a glasses-type device in order to overlay advertisements onto the user's field of vision.

[0490] The system implementing this invention is comprised of a combination of multiple technological elements to provide passersby with optimized advertisements and information in real time.

[0491] First, the terminal is equipped with a camera, which is used to acquire video information of passersby. This video information includes data such as the individual's age, gender, facial expression, clothing, and belongings. Next, the server receives the video information sent from the terminal and processes this data using image analysis tools. Specifically, it applies technologies such as facial recognition and object detection to extract the necessary personal attribute information. General deep learning libraries can be used for this process.

[0492] The acquired attribute information must be anonymized. The server uses anonymization methods to transform the data into a format that does not identify individuals. This process protects the privacy of passersby.

[0493] Furthermore, the server obtains the latest trend information from various sources via the internet. By using trend information extraction methods, it collects noteworthy topics and trends from social media and news sites. This process can also be analyzed using natural language processing technology.

[0494] Once anonymized personal attribute information and trend information are gathered, the server integrates them and generates advertisements and information using a generative AI model. The generated content is output to the visual device by a glasses-type display device control means so that the advertisement is overlaid on the user's field of view.

[0495] As a concrete example, when a user is walking through a commercial facility, promotional information and the latest product information from nearby stores are displayed on the smart glasses' screen. At this time, the information seen by the user is presented so naturally that it is as if digital signage is superimposed on the real-world scenery.

[0496] An example of a prompt when using a generative AI model is: "Generate the optimal advertising strategy to provide users who are running with real-time information on the latest sales at nearby sporting goods stores."

[0497] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0498] Step 1:

[0499] The device uses a camera to acquire video information of passersby. The input data is raw video information acquired by the camera, and the output is image data. This image data is used to identify the age, gender, facial expression, clothing, and belongings of passersby.

[0500] Step 2:

[0501] The server receives image data sent from the terminal. The input data is image data sent from the terminal, and the output is attribute information of the identified individual. Using image analysis tools and deep learning technology, the server performs the operation of identifying the personal attributes of passersby.

[0502] Step 3:

[0503] The server anonymizes the identified individual's attribute information using anonymization methods. The input data is the individual's attribute information, and the output is anonymized attribute information. In this step, an anonymization algorithm is used to protect personal information.

[0504] Step 4:

[0505] The server collects the latest trend information from sources via the internet. Input data consists of internet data feeds (social media, news sites, etc.), and output is the collected trend information. It uses trend information extraction methods and natural language processing techniques to analyze important trends.

[0506] Step 5:

[0507] The server uses a generative AI model to generate advertisements and information based on anonymized personal attribute information and trend information. The input data is anonymized personal attribute information and trend information, and the output is generated advertisement content. By inputting prompts into the generative AI model, it generates advertisements appropriate to the user.

[0508] Step 6:

[0509] The terminal receives advertising content transmitted from the server and displays the information in the user's field of view using glasses-type display device control means. The input data is the generated advertising content, and the output is the information displayed on the visual device. The display device is controlled to overlay the information in a natural manner onto the user's field of view.

[0510] 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.

[0511] This invention is a system for displaying optimized advertisements and information to passersby in real time, and further personalizes them by incorporating an emotion engine that analyzes user emotions. Each component works together to provide highly optimized content while protecting individual privacy.

[0512] First, the terminal acquires video information of passersby via a camera installed on it. The data obtained at this stage includes visual information such as the passersby's faces and clothing. The video information is transmitted to the server in real time and processed.

[0513] The server first uses an image analysis algorithm on the transmitted video data. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. It also uses an emotion engine to analyze emotions from the passersby's facial expressions. For example, it analyzes facial features to identify emotions such as "joy" or "surprise."

[0514] The acquired personal attribute information is anonymized using anonymization technology. In this process, personally identifiable information is removed and generalized, such as "a woman in her 30s with a surprised expression."

[0515] The server then collects trend information through internet-based information sources and processes this information using a trend information extraction mechanism. This mechanism uses an API to retrieve the latest trend data and extracts highly relevant information from it.

[0516] Next, anonymized attribute information, analyzed sentiment data, and trend information are integrated to generate content. Specifically, advertising themes and information that take user emotions into account are incorporated. For example, if sentiment analysis identifies a passerby as excited, an advertisement for an energetic music festival will be displayed.

[0517] Finally, the device displays the generated content on its screen. Users can see this personalized information and instantly learn about products and events relevant to them.

[0518] As a concrete example, consider a scenario where the system operates in a commercial facility. If a terminal acquires information that the user is a "man in his 40s who is smiling," and the server grasps the "trend of new gadget products," the emotion engine identifies that the user is in a positive emotional state. In this case, the server generates an advertisement for a "launch event of the latest gadgets" that is appropriate for these attributes and emotions, and the terminal displays it on its screen along with rich images. The user is intrigued by the information and can obtain more detailed information through the display.

[0519] The following describes the processing flow.

[0520] Step 1:

[0521] The terminal uses the installed camera to capture video information of passersby. This video information is recorded as a series of frames and sent to the server in a state ready for immediate processing.

[0522] Step 2:

[0523] The server performs image analysis on the received video information. Specifically, it uses a machine learning model to detect attributes such as the age, gender, clothing, and belongings of passersby.

[0524] Step 3:

[0525] The server runs an emotion engine in parallel with image analysis, identifying emotions by analyzing the facial expressions of passersby. For example, it can identify emotions such as "joy" from the degree of a smile.

[0526] Step 4:

[0527] The server anonymizes the acquired personal attribute and sentiment data. Here, information that could directly identify an individual is removed, and the data is converted into generalized data such as "a man in his 40s who is smiling."

[0528] Step 5:

[0529] The server connects to internet information sources and collects trend information. Trend information extraction methods are used to identify current trends and user interests.

[0530] Step 6:

[0531] The server integrates anonymized personal attribute information, sentiment data, and trend information, and generates advertisements or information using content generation methods. This content will also take into account the emotional state of passersby.

[0532] Step 7:

[0533] The device displays generated content received from the server on its screen. Users can view the display and receive information that aligns with their emotions and interests, and take action to obtain more detailed information as needed.

[0534] (Example 2)

[0535] 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."

[0536] Making the information and advertisements displayed to passersby more personalized and optimized in real time is a crucial challenge in providing effective information in commercial facilities and public spaces. However, building a system that efficiently presents information without infringing on privacy when handling personal information has not been easy.

[0537] 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.

[0538] In this invention, the server includes an analysis means for acquiring visual information of passersby and determining their personal attributes, a processing means for de-identifying the determined personal information, and an information extraction means for extracting trend information collected from information sources. This makes it possible to provide optimal information based on the user's emotions and tendencies while protecting privacy.

[0539] "Visual information" is a general term for data acquired visually, such as the faces, clothing, and facial expressions of passersby.

[0540] "Analysis means" refers to technologies and devices used to determine the attributes of passersby from acquired visual information.

[0541] "De-identification" is the process of transforming data into a format that makes it impossible to identify individuals.

[0542] "Processing means" refers to technologies or devices used to de-specify the results of the classification.

[0543] "Trend information" refers to data that shows the latest changes and trends in a specific theme or market.

[0544] "Information extraction means" refers to technologies and devices used to collect trend information from information sources and extract necessary elements.

[0545] "Generation means" refers to technologies and devices for creating relevant content based on anonymized attribute information and trend information.

[0546] "Control means" refers to technologies and devices that are responsible for displaying the generated content on an output device.

[0547] A "generative AI model" is a set of algorithms and datasets used to dynamically generate content using machine learning.

[0548] The system of this invention is primarily intended to provide optimized advertisements and information to passersby in real time, mainly in commercial facilities and public spaces. The entire system consists of three main elements: terminals, servers, and users.

[0549] The terminal first uses a high-resolution camera to acquire visual information about passersby. Hardware used includes digital cameras and video acquisition devices, and the video data is captured in a format that allows for real-time processing.

[0550] The server then uses image analysis libraries such as OpenCV and TensorFlow to determine the age, gender, clothing, facial expression, and belongings of passersby from the video information. Furthermore, an emotion engine analyzes the facial expressions to identify the user's emotions. The analysis results are then anonymized to a format that does not allow for the identification of individuals. Appropriate consideration is given to respecting individual privacy during this process.

[0551] The server is also responsible for collecting trend information from the internet. APIs are used for information extraction, including current events and data from online platforms. This information is kept constantly up-to-date.

[0552] The generative AI model combines anonymized personal attribute information, analyzed sentiment data, and trend information to generate personalized advertisements and informational content. This algorithm allows, for example, to prioritize providing information on relevant music or sporting events if a user is excited.

[0553] A concrete example is when a device acquires information such as "a man in his 40s who is smiling." In this case, the server grasps the "trend of new gadget products," and the generative AI model generates information about "launch events for the latest gadgets." The device displays this information on its screen, and the user can obtain further details from the display.

[0554] An example of a prompt message would be: "Generate an ad for a smiling man in his 40s, taking into account the latest gadget trends."

[0555] Therefore, this system can maximize the effectiveness of information provision in facilities and stores by providing valuable information to users and attracting their interest.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] The device uses a high-resolution camera to acquire visual information about passersby. The input is real-time video data including the passersby's faces, clothing, and facial expressions. This data is pre-processed so that it can be instantly transmitted to the server.

[0559] Step 2:

[0560] The server processes the received video data through an image analysis algorithm. The input is raw video data sent from the terminal, and the output is the identification results of the age, gender, clothing, facial expression, and belongings of passersby. Here, an image recognition library is used to perform face recognition and object classification to identify each attribute.

[0561] Step 3:

[0562] The server anonymizes the analyzed personal attribute information. The input is already identified attribute information, and the output is anonymized data from which the ability to identify an individual has been removed. For example, it is converted into a generalized format such as "a woman in her 30s, wearing casual clothes."

[0563] Step 4:

[0564] The server collects trend information using an internet API. The input is unorganized data from multiple sources, and the output is the latest extracted trend information. At this stage, text analysis is performed to efficiently process the trend information.

[0565] Step 5:

[0566] The content generation method utilizes a generative AI model to integrate anonymized attribute information, analyzed sentiment data, and trend information. The input is a combination of these data, and the output is advertisements and informational content that reflect the user's emotions and preferences. For example, if the user is identified as smiling, a friendly product promotion will be created.

[0567] Step 6:

[0568] The terminal displays the generated content on its screen. The input is pre-generated content sent from the server, and the output is visual information displayed to the user. Specifically, presentations are given using vivid images and videos, and the user can receive information directly from the display.

[0569] (Application Example 2)

[0570] 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."

[0571] Modern advertising and information display systems are insufficiently personalized based on the emotions and attributes of individual passersby. Furthermore, there is a need for means of directly displaying information tailored to the individual through personal devices, particularly smart glasses. This invention aims to provide real-time optimized advertising within the user's visual field, based on their individual emotional state and trend information.

[0572] 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.

[0573] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to display surrounding information in the passerby's field of vision in real time via a visual interface.

[0574] "Video information of passersby" refers to visual data recorded by cameras or other devices showing people passing through a specific location.

[0575] "Image analysis means" refers to technology used to identify individual attributes such as age, gender, facial expression, clothing, and possessions from video information.

[0576] An "anonymization method" is a process for converting acquired personal information into a format in which the individual cannot be identified.

[0577] A "trend information extraction method" is a technology that collects and analyzes the latest trend information from information sources such as the internet.

[0578] "Content generation methods" refer to technologies that create optimal advertisements and information based on anonymized personal attribute information and trend information.

[0579] "Display control means" refers to control technology for outputting generated advertisements and information to a designated display.

[0580] "Visual output means" refers to technologies that display information directly in the user's field of vision through devices such as smart glasses.

[0581] This invention is a system that displays optimized advertisements based on specific attribute information and emotional states of passersby. It consists of three roles: server, terminal, and user.

[0582] The server acquires video information of passersby from cameras built into smart glasses or similar devices. Using image analysis technologies such as OpenCV and TensorFlow, it identifies the age, gender, facial expression, clothing, and belongings of passersby and anonymizes this information. Based on the anonymized information, it collects current events and trend data from information sources via APIs in order to extract trend information. Based on this information, it uses content generation tools to generate advertisements and information optimized for the attributes and emotions of passersby.

[0583] The device is a smart glasses or other device worn by the user, which displays content received from a server in real time within the user's field of vision through visual output means. This allows the user to intuitively obtain the information and advertisements most relevant to them.

[0584] As a concrete example, consider a male user in his 40s walking through a town where a new cafe has opened. If this user smiles, the camera recognizes his emotional state, and the server identifies the new cafe's opening information. It then generates an appropriate advertisement and displays an offer of "free new cappuccino" on the user's smart glasses. In this way, users can instantly obtain local information and become interested in it.

[0585] An example of a prompt sentence to input into a generative AI model is, "What kind of advertisement would be appropriate to display in the street when a man in his 40s is smiling?"

[0586] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0587] Step 1:

[0588] The device acquires real-time video information of passersby using its built-in camera. The image data captured by the camera is used as input.

[0589] Step 2:

[0590] The server receives video information transmitted from the terminal and performs image analysis using OpenCV. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. The identified attribute information is then output.

[0591] Step 3:

[0592] The server analyzes emotions from facial expressions identified using TensorFlow. Facial expression data is used as input, and emotional information such as joy or surprise is output through the analysis.

[0593] Step 4:

[0594] The server converts the identified attribute and sentiment information into a format that does not identify individuals using anonymization methods. Attribute and sentiment information are used as input, and anonymized data is output.

[0595] Step 5:

[0596] The server collects the latest trend information from the internet via an API. The acquired data is processed by a trend information extraction method, and highly relevant trend information is output.

[0597] Step 6:

[0598] The server receives anonymized attribute information, sentiment information, and trend information as input, and generates optimized advertising content using content generation methods. The generated advertising content is then output.

[0599] Step 7:

[0600] The device receives advertising content transmitted from the server and displays it within the user's field of view using visual output means. Information optimized for the user is delivered specifically.

[0601] Step 8:

[0602] Users review the advertising content displayed on their device and take actions to obtain more detailed information as needed. This allows them to instantly grasp information that interests them.

[0603] 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.

[0604] 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.

[0605] 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.

[0606] [Fourth Embodiment]

[0607] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0608] 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.

[0609] 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).

[0610] 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.

[0611] 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.

[0612] 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).

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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".

[0620] This invention is a digital signage system for displaying optimized advertisements and information to passersby in real time. Each element works in conjunction to enable the generation and display of personalized content while avoiding the identification of personal information.

[0621] First, the terminal uses cameras installed on streets and in commercial facilities to acquire video information of passersby. This video information is transmitted to the server in real time. After receiving this video information, the server uses image analysis technology to identify personal attributes of passersby, such as age, gender, facial expression, clothing, and belongings.

[0622] Next, the server uses anonymization techniques to de-identify the identified personal attribute information. This process transforms the personal data into generalized attribute information such as "male in his 20s" or "casual clothing."

[0623] The server then extracts the latest trend information from internet sources, such as social media feeds and news sites. This information is analyzed in real time and used to identify important trends and topics.

[0624] Once anonymized attribute information and trend information are gathered, the server integrates them to generate advertisements or informational content optimized for passersby. The generated content is selected based on the passersby's attributes, and specific advertising themes are extracted.

[0625] Ultimately, the terminal receives content transmitted from the server and displays it on the digital signage. As a result, passersby can see advertisements and information tailored to their interests and needs in real time.

[0626] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose a terminal analyzes attributes such as "a woman in her 30s wearing sportswear," and the server determines that "fitness and health products" are attracting attention as a recent trend. In this case, the server generates an advertisement containing "sale information on the latest fitness wear" based on these attributes and trend information, and the terminal displays it on digital signage. The user can then see this information and instantly obtain highly relevant products and sales information.

[0627] The following describes the processing flow.

[0628] Step 1:

[0629] The terminal uses the installed camera to capture video information of passersby. This information is acquired as a series of frames and is ready for processing in real time.

[0630] Step 2:

[0631] The server receives video data transmitted from the terminal. To analyze the received data, it performs image analysis using computer vision technology to identify attributes such as the age, gender, facial expression, clothing, and belongings of passersby.

[0632] Step 3:

[0633] The server processes the identified personal attributes using anonymization methods. Specifically, any information that could identify an individual is removed and converted into abstract data such as "male in his 20s" or "business casual attire."

[0634] Step 4:

[0635] The server accesses information sources on the internet and collects the latest trend information using trend information extraction methods. This is a process of collecting data from social media and news sites via APIs and extracting important trends from it.

[0636] Step 5:

[0637] The server integrates anonymized personal attribute information with extracted trend information and generates advertisements or information using content generation methods. The generated content is tailored to the individual's attributes, and specific content such as "Fitness Product Sale" is created.

[0638] Step 6:

[0639] The device receives generated content sent from the server. This content is output to a display device such as a screen and shown to passersby in real time. Users can view the displayed information and receive advertisements and information relevant to them.

[0640] (Example 1)

[0641] 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".

[0642] Modern advertising systems require the real-time delivery of information and advertisements tailored to the interests and needs of passersby. However, providing individually optimized content while maintaining privacy and avoiding personal identification is challenging. Furthermore, rapidly incorporating the latest trends is necessary to enhance advertising effectiveness, but utilizing such dynamic information is technically difficult. Therefore, building systems that provide personalized advertising and information while protecting privacy is a crucial challenge.

[0643] 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.

[0644] In this invention, the server includes data analysis means for acquiring image data of passersby and determining their personal attributes; data anonymization means for de-specificating the determined attribute information and converting it into a format that makes personal identification impossible; and information extraction means for acquiring trend information collected from information sources and identifying important topics. This makes it possible to provide advertisements and information tailored to the interests and needs of passersby in real time while protecting their privacy.

[0645] "Acquiring image data of passersby" means collecting video information of passersby in real time using imaging devices installed on streets and in commercial facilities.

[0646] "Identifying individual attributes" means analyzing received image data and identifying information such as age, gender, and clothing to determine individual characteristics.

[0647] "Data anonymization" is the process of converting identified individual attribute information into a format that does not identify a specific individual.

[0648] "Acquiring trend information collected from information sources" means seeking the latest topics and trends as data in real time from various information platforms on the internet.

[0649] "Identifying important topics" means identifying themes and topics that are currently attracting attention from the collected trending information.

[0650] "Generating personalized information" means creating contextually relevant advertisements and informational content based on anonymized personal attribute information and trend information.

[0651] "Outputting to a video display device" means transmitting generated advertisements or information to a device such as a display.

[0652] This invention is a system aimed at providing personalized advertisements and information to passersby in real time. The system uses advanced digital signage devices installed on streets and in commercial facilities to display advertisements that reflect the interests and needs of passersby.

[0653] The terminal uses high-resolution cameras installed in commercial facilities and public spaces to acquire image data of passersby. The acquired image data is transmitted to a server via a secure network, where data analysis is performed. In the data analysis, image analysis techniques (specifically, software libraries such as OpenCV and TensorFlow) are used to identify characteristics of passersby such as age, gender, clothing, facial expression, and belongings.

[0654] The server processes the analyzed personal attribute information using anonymization techniques (e.g., k-anonymization) to transform it into a format that makes it impossible to identify individuals while protecting privacy. The server also utilizes current events information and social media data collected from the internet to obtain the latest trend information. Natural language processing techniques (e.g., NLTK and spaCy) can be used in this process.

[0655] By integrating this information, the server uses a generative AI model (GPT-4, for example) to generate personalized advertising content optimized for passersby. The generated content is sent to the device and displayed on digital signage. As a result, passersby can see information tailored to their interests and needs in real time, leading to a higher level of satisfaction.

[0656] As a concrete example, consider a scenario where the system is operating in a shopping mall. Suppose the terminal analyzes attributes such as "a woman in her 30s wearing casual clothing," and the server identifies "eco-friendly products" as a current trend. In this case, the server can generate an advertisement containing "sale information on the latest eco-bags," which the terminal can then display on digital signage.

[0657] Examples of prompts to input into a generative AI model:

[0658] "Please create an advertisement targeting casually dressed women in their 30s, incorporating the latest trends in eco-friendly products."

[0659] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0660] Step 1:

[0661] The terminal acquires real-time image data of passersby using cameras installed on streets and in commercial facilities. This input image data must be high resolution, clearly showing details such as the faces and postures of passersby. This prepares the system for accurate image analysis in the next step.

[0662] Step 2:

[0663] The device transmits the acquired image data to the server via SSL / TLS encrypted communication. A secure communication protocol is used during this transmission process to ensure data confidentiality. As a result, anonymity is ensured, and personally identifiable information is protected until it reaches the server.

[0664] Step 3:

[0665] The server analyzes the received image data using OpenCV and TensorFlow. By running image processing algorithms on the input images, it identifies personal attributes such as the age, gender, clothing, and facial expressions of passersby. The output is this attribute information.

[0666] Step 4:

[0667] The server de-identifies identified personal attribute information using k-anonymization technology. This process generalizes individual attribute data into categories such as "male in his 20s" or "casual clothing." The output is attribute data in a format that does not identify individuals.

[0668] Step 5:

[0669] The server collects the latest trending information from internet sources. Input data includes Google News and social media feeds, which are analyzed using natural language processing technologies (such as NLTK and spaCy) to extract noteworthy trends. The output is trend information reflecting current popular themes.

[0670] Step 6:

[0671] The server integrates anonymized personal attribute information and trend information, and uses a generative AI model (such as GPT-4) to generate personalized advertising content. This prompt-based generation outputs optimized ads that take attribute information and trends into account.

[0672] Step 7:

[0673] The terminal receives the generated advertising content and displays it on the digital signage. This allows passersby to see information tailored to their interests and needs in real time. The output is the displayed advertisements and information.

[0674] (Application Example 1)

[0675] 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".

[0676] There is a need for systems that display advertisements and information optimized for passersby in real time on streets and in commercial facilities. However, providing advertisements that match the interests and needs of passersby without identifying their personal information is not easy. Furthermore, in order to display advertisements efficiently, a method is needed to deliver information directly to the passersby's perspective. Since conventional technologies have difficulty providing such personalized information, the development of more effective methods is desired.

[0677] 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.

[0678] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to overlay advertisements onto the user's field of view.

[0679] "Image analysis means" refers to a processing device for determining an individual's age, gender, facial expression, clothing, and belongings from video information of passersby.

[0680] An "anonymization method" is a technology that protects privacy by converting identified individual attribute information into a form that makes it impossible to identify the individual.

[0681] A "trend information extraction method" is a mechanism for collecting, analyzing, and extracting the latest trend information from various sources.

[0682] A "content generation method" is a device that generates appropriate advertisements and information for passersby based on anonymized personal attribute information and trend information.

[0683] "Display control means" refers to a control unit that outputs the generated advertisement or information to a visual device for passersby to see.

[0684] The "glasses-type display device control means" is a mechanism that controls a glasses-type device in order to overlay advertisements onto the user's field of vision.

[0685] The system implementing this invention is comprised of a combination of multiple technological elements to provide passersby with optimized advertisements and information in real time.

[0686] First, the terminal is equipped with a camera, which is used to acquire video information of passersby. This video information includes data such as the individual's age, gender, facial expression, clothing, and belongings. Next, the server receives the video information sent from the terminal and processes this data using image analysis tools. Specifically, it applies technologies such as facial recognition and object detection to extract the necessary personal attribute information. General deep learning libraries can be used for this process.

[0687] The acquired attribute information must be anonymized. The server uses anonymization methods to transform the data into a format that does not identify individuals. This process protects the privacy of passersby.

[0688] Furthermore, the server obtains the latest trend information from various sources via the internet. By using trend information extraction methods, it collects noteworthy topics and trends from social media and news sites. This process can also be analyzed using natural language processing technology.

[0689] Once anonymized personal attribute information and trend information are gathered, the server integrates them and generates advertisements and information using a generative AI model. The generated content is output to the visual device by a glasses-type display device control means so that the advertisement is overlaid on the user's field of view.

[0690] As a concrete example, when a user is walking through a commercial facility, promotional information and the latest product information from nearby stores are displayed on the smart glasses' screen. At this time, the information seen by the user is presented so naturally that it is as if digital signage is superimposed on the real-world scenery.

[0691] An example of a prompt when using a generative AI model is: "Generate the optimal advertising strategy to provide users who are running with real-time information on the latest sales at nearby sporting goods stores."

[0692] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0693] Step 1:

[0694] The device uses a camera to acquire video information of passersby. The input data is raw video information acquired by the camera, and the output is image data. This image data is used to identify the age, gender, facial expression, clothing, and belongings of passersby.

[0695] Step 2:

[0696] The server receives image data sent from the terminal. The input data is image data sent from the terminal, and the output is attribute information of the identified individual. Using image analysis tools and deep learning technology, the server performs the operation of identifying the personal attributes of passersby.

[0697] Step 3:

[0698] The server anonymizes the identified individual's attribute information using anonymization methods. The input data is the individual's attribute information, and the output is anonymized attribute information. In this step, an anonymization algorithm is used to protect personal information.

[0699] Step 4:

[0700] The server collects the latest trend information from sources via the internet. Input data consists of internet data feeds (social media, news sites, etc.), and output is the collected trend information. It uses trend information extraction methods and natural language processing techniques to analyze important trends.

[0701] Step 5:

[0702] The server uses a generative AI model to generate advertisements and information based on anonymized personal attribute information and trend information. The input data is anonymized personal attribute information and trend information, and the output is generated advertisement content. By inputting prompts into the generative AI model, it generates advertisements appropriate to the user.

[0703] Step 6:

[0704] The terminal receives advertising content transmitted from the server and displays the information in the user's field of view using glasses-type display device control means. The input data is the generated advertising content, and the output is the information displayed on the visual device. The display device is controlled to overlay the information in a natural manner onto the user's field of view.

[0705] 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.

[0706] This invention is a system for displaying optimized advertisements and information to passersby in real time, and further personalizes them by incorporating an emotion engine that analyzes user emotions. Each component works together to provide highly optimized content while protecting individual privacy.

[0707] First, the terminal acquires video information of passersby via a camera installed on it. The data obtained at this stage includes visual information such as the passersby's faces and clothing. The video information is transmitted to the server in real time and processed.

[0708] The server first uses an image analysis algorithm on the transmitted video data. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. It also uses an emotion engine to analyze emotions from the passersby's facial expressions. For example, it analyzes facial features to identify emotions such as "joy" or "surprise."

[0709] The acquired personal attribute information is anonymized using anonymization technology. In this process, personally identifiable information is removed and generalized, such as "a woman in her 30s with a surprised expression."

[0710] The server then collects trend information through internet-based information sources and processes this information using a trend information extraction mechanism. This mechanism uses an API to retrieve the latest trend data and extracts highly relevant information from it.

[0711] Next, anonymized attribute information, analyzed sentiment data, and trend information are integrated to generate content. Specifically, advertising themes and information that take user emotions into account are incorporated. For example, if sentiment analysis identifies a passerby as excited, an advertisement for an energetic music festival will be displayed.

[0712] Finally, the device displays the generated content on its screen. Users can see this personalized information and instantly learn about products and events relevant to them.

[0713] As a concrete example, consider a scenario where the system operates in a commercial facility. If a terminal acquires information that the user is a "man in his 40s who is smiling," and the server grasps the "trend of new gadget products," the emotion engine identifies that the user is in a positive emotional state. In this case, the server generates an advertisement for a "launch event of the latest gadgets" that is appropriate for these attributes and emotions, and the terminal displays it on its screen along with rich images. The user is intrigued by the information and can obtain more detailed information through the display.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The terminal uses the installed camera to capture video information of passersby. This video information is recorded as a series of frames and sent to the server in a state ready for immediate processing.

[0717] Step 2:

[0718] The server performs image analysis on the received video information. Specifically, it uses a machine learning model to detect attributes such as the age, gender, clothing, and belongings of passersby.

[0719] Step 3:

[0720] The server runs an emotion engine in parallel with image analysis, identifying emotions by analyzing the facial expressions of passersby. For example, it can identify emotions such as "joy" from the degree of a smile.

[0721] Step 4:

[0722] The server anonymizes the acquired personal attribute and sentiment data. Here, information that could directly identify an individual is removed, and the data is converted into generalized data such as "a man in his 40s who is smiling."

[0723] Step 5:

[0724] The server connects to internet information sources and collects trend information. Trend information extraction methods are used to identify current trends and user interests.

[0725] Step 6:

[0726] The server integrates anonymized personal attribute information, sentiment data, and trend information, and generates advertisements or information using content generation methods. This content will also take into account the emotional state of passersby.

[0727] Step 7:

[0728] The device displays generated content received from the server on its screen. Users can view the display and receive information that aligns with their emotions and interests, and take action to obtain more detailed information as needed.

[0729] (Example 2)

[0730] 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".

[0731] Making the information and advertisements displayed to passersby more personalized and optimized in real time is a crucial challenge in providing effective information in commercial facilities and public spaces. However, building a system that efficiently presents information without infringing on privacy when handling personal information has not been easy.

[0732] 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.

[0733] In this invention, the server includes an analysis means for acquiring visual information of passersby and determining their personal attributes, a processing means for de-identifying the determined personal information, and an information extraction means for extracting trend information collected from information sources. This makes it possible to provide optimal information based on the user's emotions and tendencies while protecting privacy.

[0734] "Visual information" is a general term for data acquired visually, such as the faces, clothing, and facial expressions of passersby.

[0735] "Analysis means" refers to technologies and devices used to determine the attributes of passersby from acquired visual information.

[0736] "De-identification" is the process of transforming data into a format that makes it impossible to identify individuals.

[0737] "Processing means" refers to technologies or devices used to de-specify the results of the classification.

[0738] "Trend information" refers to data that shows the latest changes and trends in a specific theme or market.

[0739] "Information extraction means" refers to technologies and devices used to collect trend information from information sources and extract necessary elements.

[0740] "Generation means" refers to technologies and devices for creating relevant content based on anonymized attribute information and trend information.

[0741] "Control means" refers to technologies and devices that are responsible for displaying the generated content on an output device.

[0742] A "generative AI model" is a set of algorithms and datasets used to dynamically generate content using machine learning.

[0743] The system of this invention is primarily intended to provide optimized advertisements and information to passersby in real time, mainly in commercial facilities and public spaces. The entire system consists of three main elements: terminals, servers, and users.

[0744] The terminal first uses a high-resolution camera to acquire visual information about passersby. Hardware used includes digital cameras and video acquisition devices, and the video data is captured in a format that allows for real-time processing.

[0745] The server then uses image analysis libraries such as OpenCV and TensorFlow to determine the age, gender, clothing, facial expression, and belongings of passersby from the video information. Furthermore, an emotion engine analyzes the facial expressions to identify the user's emotions. The analysis results are then anonymized to a format that does not allow for the identification of individuals. Appropriate consideration is given to respecting individual privacy during this process.

[0746] The server is also responsible for collecting trend information from the internet. APIs are used for information extraction, including current events and data from online platforms. This information is kept constantly up-to-date.

[0747] The generative AI model combines anonymized personal attribute information, analyzed sentiment data, and trend information to generate personalized advertisements and informational content. This algorithm allows, for example, to prioritize providing information on relevant music or sporting events if a user is excited.

[0748] A concrete example is when a device acquires information such as "a man in his 40s who is smiling." In this case, the server grasps the "trend of new gadget products," and the generative AI model generates information about "launch events for the latest gadgets." The device displays this information on its screen, and the user can obtain further details from the display.

[0749] An example of a prompt message would be: "Generate an ad for a smiling man in his 40s, taking into account the latest gadget trends."

[0750] Therefore, this system can maximize the effectiveness of information provision in facilities and stores by providing valuable information to users and attracting their interest.

[0751] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0752] Step 1:

[0753] The device uses a high-resolution camera to acquire visual information about passersby. The input is real-time video data including the passersby's faces, clothing, and facial expressions. This data is pre-processed so that it can be instantly transmitted to the server.

[0754] Step 2:

[0755] The server processes the received video data through an image analysis algorithm. The input is raw video data sent from the terminal, and the output is the identification results of the age, gender, clothing, facial expression, and belongings of passersby. Here, an image recognition library is used to perform face recognition and object classification to identify each attribute.

[0756] Step 3:

[0757] The server anonymizes the analyzed personal attribute information. The input is already identified attribute information, and the output is anonymized data from which the ability to identify an individual has been removed. For example, it is converted into a generalized format such as "a woman in her 30s, wearing casual clothes."

[0758] Step 4:

[0759] The server collects trend information using an internet API. The input is unorganized data from multiple sources, and the output is the latest extracted trend information. At this stage, text analysis is performed to efficiently process the trend information.

[0760] Step 5:

[0761] The content generation method utilizes a generative AI model to integrate anonymized attribute information, analyzed sentiment data, and trend information. The input is a combination of these data, and the output is advertisements and informational content that reflect the user's emotions and preferences. For example, if the user is identified as smiling, a friendly product promotion will be created.

[0762] Step 6:

[0763] The terminal displays the generated content on its screen. The input is pre-generated content sent from the server, and the output is visual information displayed to the user. Specifically, presentations are given using vivid images and videos, and the user can receive information directly from the display.

[0764] (Application Example 2)

[0765] 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".

[0766] Modern advertising and information display systems are insufficiently personalized based on the emotions and attributes of individual passersby. Furthermore, there is a need for means of directly displaying information tailored to the individual through personal devices, particularly smart glasses. This invention aims to provide real-time optimized advertising within the user's visual field, based on their individual emotional state and trend information.

[0767] 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.

[0768] In this invention, the server includes image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings; anonymization means for anonymizing the determined individual's attribute information and converting it into a format that does not identify the individual; and trend information extraction means for extracting the latest trend information collected from information sources. This makes it possible to display surrounding information in the passerby's field of vision in real time via a visual interface.

[0769] "Video information of passersby" refers to visual data recorded by cameras or other devices showing people passing through a specific location.

[0770] "Image analysis means" refers to technology used to identify individual attributes such as age, gender, facial expression, clothing, and possessions from video information.

[0771] An "anonymization method" is a process for converting acquired personal information into a format in which the individual cannot be identified.

[0772] A "trend information extraction method" is a technology that collects and analyzes the latest trend information from information sources such as the internet.

[0773] "Content generation methods" refer to technologies that create optimal advertisements and information based on anonymized personal attribute information and trend information.

[0774] "Display control means" refers to control technology for outputting generated advertisements and information to a designated display.

[0775] "Visual output means" refers to technologies that display information directly in the user's field of vision through devices such as smart glasses.

[0776] This invention is a system that displays optimized advertisements based on specific attribute information and emotional states of passersby. It consists of three roles: server, terminal, and user.

[0777] The server acquires video information of passersby from cameras built into smart glasses or similar devices. Using image analysis technologies such as OpenCV and TensorFlow, it identifies the age, gender, facial expression, clothing, and belongings of passersby and anonymizes this information. Based on the anonymized information, it collects current events and trend data from information sources via APIs in order to extract trend information. Based on this information, it uses content generation tools to generate advertisements and information optimized for the attributes and emotions of passersby.

[0778] The device is a smart glasses or other device worn by the user, which displays content received from a server in real time within the user's field of vision through visual output means. This allows the user to intuitively obtain the information and advertisements most relevant to them.

[0779] As a concrete example, consider a male user in his 40s walking through a town where a new cafe has opened. If this user smiles, the camera recognizes his emotional state, and the server identifies the new cafe's opening information. It then generates an appropriate advertisement and displays an offer of "free new cappuccino" on the user's smart glasses. In this way, users can instantly obtain local information and become interested in it.

[0780] An example of a prompt sentence to input into a generative AI model is, "What kind of advertisement would be appropriate to display in the street when a man in his 40s is smiling?"

[0781] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0782] Step 1:

[0783] The device acquires real-time video information of passersby using its built-in camera. The image data captured by the camera is used as input.

[0784] Step 2:

[0785] The server receives video information transmitted from the terminal and performs image analysis using OpenCV. Here, it identifies the age, gender, facial expression, clothing, and belongings of passersby. The identified attribute information is then output.

[0786] Step 3:

[0787] The server analyzes emotions from facial expressions identified using TensorFlow. Facial expression data is used as input, and emotional information such as joy or surprise is output through the analysis.

[0788] Step 4:

[0789] The server converts the identified attribute and sentiment information into a format that does not identify individuals using anonymization methods. Attribute and sentiment information are used as input, and anonymized data is output.

[0790] Step 5:

[0791] The server collects the latest trend information from the internet via an API. The acquired data is processed by a trend information extraction method, and highly relevant trend information is output.

[0792] Step 6:

[0793] The server receives anonymized attribute information, sentiment information, and trend information as input, and generates optimized advertising content using content generation methods. The generated advertising content is then output.

[0794] Step 7:

[0795] The device receives advertising content transmitted from the server and displays it within the user's field of view using visual output means. Information optimized for the user is delivered specifically.

[0796] Step 8:

[0797] Users review the advertising content displayed on their device and take actions to obtain more detailed information as needed. This allows them to instantly grasp information that interests them.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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."

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0819] The following is further disclosed regarding the embodiments described above.

[0820] (Claim 1)

[0821] Image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings,

[0822] An anonymization method that anonymizes the attribute information of identified individuals and converts it into a format that does not allow for the identification of individuals,

[0823] A trend information extraction method that extracts the latest trend information collected from information sources,

[0824] A content generation method that generates advertisements or information by combining anonymized personal attribute information and trend information,

[0825] A display control means that outputs the generated advertisement or information to a display device,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, further comprising a content selection means that generates content to select specific advertising content based on personal attributes determined from acquired video information.

[0829] (Claim 3)

[0830] The system according to claim 1, wherein the trend information collected includes current events information and data from information exchange networks.

[0831] "Example 1"

[0832] (Claim 1)

[0833] A data analysis method that acquires image data of passersby and identifies individual attributes,

[0834] A data anonymization method that de-identifies identified attribute information and converts it into a format that makes personal identification impossible,

[0835] Information extraction means for obtaining trend information collected from information sources and identifying important topics,

[0836] A content generation method that integrates anonymized attribute information and trend information to generate personalized information,

[0837] An output control means that outputs the generated information to a video display device,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, further comprising content selection means for which generated information selects an advertising subject based on analyzed attributes.

[0841] (Claim 3)

[0842] The system according to claim 1, wherein the collected trend information includes current events information and data from a communication network.

[0843] "Application Example 1"

[0844] (Claim 1)

[0845] Image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings,

[0846] An anonymization method that anonymizes the attribute information of identified individuals and converts it into a format that does not allow for the identification of individuals,

[0847] A trend information extraction method that extracts the latest trend information collected from information sources,

[0848] A content generation method that generates advertisements or information by combining anonymized personal attribute information and trend information,

[0849] A display control means that outputs the generated advertisement or information to a visual device,

[0850] A glasses-type display device control means for overlaying advertisements onto the user's field of view,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, further comprising a content selection means that generates content to select specific advertising content based on personal attributes determined from acquired video information.

[0854] (Claim 3)

[0855] The system according to claim 1, wherein the trend information collected includes current events information and data from information exchange networks.

[0856] "Example 2 of combining an emotion engine"

[0857] (Claim 1)

[0858] An analytical method for acquiring visual information of passersby and determining their individual attributes,

[0859] A processing method for de-identifying the identified individual's information,

[0860] Information extraction means for extracting trend information collected from information sources,

[0861] A generation means that generates content by combining anonymized attribute information and trend information,

[0862] A control means for displaying the generated content on an output device,

[0863] An analytical method that analyzes user emotions to achieve personalization,

[0864] A model application means for dynamically generating content using a generative AI model,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, further comprising a selection means that selects specific advertising content based on personal information determined from acquired visual information.

[0868] (Claim 3)

[0869] The system according to claim 1, wherein the trend information collected includes current events information and data from information networks.

[0870] "Application example 2 when combining with an emotional engine"

[0871] (Claim 1)

[0872] Image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings,

[0873] An anonymization method that anonymizes the attribute information of identified individuals and converts it into a format that does not allow for the identification of individuals,

[0874] A trend information extraction method that extracts the latest trend information collected from information sources,

[0875] A content generation method that generates advertisements or information by combining anonymized personal attribute information and trend information,

[0876] A display control means that outputs the generated advertisement or information to a display device,

[0877] A visual output means that displays surrounding information in real time within the visual field of passersby via a visual interface,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, further comprising a content selection means that generates content to select specific advertising content based on personal attributes determined from acquired video information.

[0881] (Claim 3)

[0882] The system according to claim 1, wherein the trend information collected includes current events information and data from information exchange networks. [Explanation of Symbols]

[0883] 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. Image analysis means for acquiring video information of passersby and determining the individual's age, gender, facial expression, clothing, and belongings, An anonymization method that anonymizes the attribute information of identified individuals and converts it into a format that does not allow for the identification of individuals, A trend information extraction method that extracts the latest trend information collected from information sources, A content generation method that generates advertisements or information by combining anonymized personal attribute information and trend information, A display control means that outputs the generated advertisement or information to a display device, A system that includes this.

2. The system according to claim 1, further comprising content selection means that generates content to select specific advertising content based on personal attributes determined from acquired video information.

3. The system according to claim 1, wherein the trend information collected includes current events information and data from information exchange networks.

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