System

Abstract

An object of the system according to the embodiment is to display an advertisement personalized to a specific target person in real time.SOLUTION: A system includes a personal information collection part, a position information collection part, an advertisement generation part, and an advertisement display part. The personal information collection unit collects personal information. The position information collection unit collects position information. The advertisement generation unit generates an advertisement based on the personal information and the position information collected by the personal information collection unit and the position information collection unit. The advertisement display unit displays the advertisement generated by the advertisement generation unit on the digital signage.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional technology, it was difficult to ensure that digital signage advertisements around town were seen by specific target audiences.

[0005] The system according to the embodiment aims to display personalized advertisements to specific target audiences in real time. [Means for solving the problem]

[0006] A system according to an embodiment includes a personal information collection unit, a location information collection unit, an advertisement generation unit, and an advertisement display unit. The personal information collection unit collects personal information. The location information collection unit collects location information. The advertisement generation unit generates an advertisement based on the personal information and location information collected by the personal information collection unit and the location information collection unit. The advertisement display unit displays the advertisement generated by the advertisement generation unit on digital signage. [Effects of the Invention]

[0007] The system according to the embodiment can display personalized advertisements to specific audiences in real time. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices 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), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The advertisement generation system according to an embodiment of the present invention is a system that generates personalized advertisements in real time not only for online advertisements but also for digital signage around town by having a generation AI learn the personal information and location information of Yahoo! JAPAN IDs. This allows the advertisement generation system to generate personalized advertisements in real time based on personal information and location information and display them on digital signage.

[0029] An advertisement generation system according to an embodiment includes a personal information collection unit, a location information collection unit, an advertisement generation unit, and an advertisement display unit. The personal information collection unit collects personal information. For example, the personal information collection unit collects a user's name, age, gender, and contact information. The personal information collection unit may also collect information related to the user's interests. The personal information collection unit may also collect information based on the user's purchase history and social media activity. The location information collection unit collects location information. For example, the location information collection unit collects GPS data. The location information collection unit may also collect Wi-Fi location information. The location information collection unit may also collect beacon data. The advertisement generation unit generates an advertisement based on the personal information and location information collected by the personal information collection unit and the location information collection unit. For example, the advertisement generation unit generates a personalized advertisement based on the user's personal information and location information using a generation AI. The advertisement generation unit may also customize the advertisement based on the user's interests. The advertisement generation unit may also generate an advertisement based on the user's current location. The advertisement display unit displays the advertisement generated by the advertisement generation unit on a digital signage. For example, the advertisement display unit displays advertisements on digital signage throughout the city. The advertisement display unit can also display advertisements on digital signage installed in specific areas or locations. The advertisement display unit can also update and display advertisements in real time. This allows the advertisement generation system to generate personalized advertisements based on personal information and location information in real time and display them on digital signage.

[0030] The advertisement generation unit can combine a user's past movement history and purchase history to predict future behavior and generate advertisements based on that prediction. The advertisement generation unit, for example, analyzes a user's past movement history and finds specific patterns. For example, for a user who visits a specific shopping mall every weekend, it generates advertisements for stores in that mall. The advertisement generation unit also analyzes a user's purchase history and generates relevant advertisements based on products and services purchased in the past. For example, for a user who has previously purchased sporting goods, it generates an advertisement for a new sporting event. The advertisement generation unit also combines the movement history and purchase history to predict a user's future behavior and generate advertisements based on that prediction. For example, for a user who is likely to participate in an event in a specific area, it generates an advertisement for that event. This makes it possible to predict future behavior based on a user's past behavior data and generate more effective advertisements.

[0031] The ad generation unit analyzes a user's social media activity and can reflect changes in interests in real time. For example, the ad generation unit analyzes a user's social media posts to detect changes in interests. For example, if a user has started to take up a new hobby or interest, the ad generation unit generates an ad related to that hobby. The ad generation unit also analyzes a user's following and like history on social media to identify trends in interests. For example, if a user shows increasing interest in a particular brand or product, the ad generation unit generates an ad for that brand. The ad generation unit also monitors a user's social media activity in real time and immediately reflects changes in interests. For example, if a user shows interest in a new event or campaign, the ad generation unit generates an ad for that event. This allows changes in interests to be reflected in real time based on the user's social media activity, thereby improving the effectiveness of advertising.

[0032] The advertisement generation unit can collect health data of a user and generate advertisements according to the user's health condition. The advertisement generation unit, for example, analyzes data from a fitness tracker to understand the user's exercise habits and health condition. For example, for a user who exercises regularly, the advertisement generation unit generates advertisements for sports equipment and fitness gyms. The advertisement generation unit also generates advertisements according to the user's health condition based on the health data. For example, for a user who is sleep-deprived, the advertisement generation unit generates advertisements for sleep aids and relaxation services. The advertisement generation unit also monitors the user's health data in real time and generates advertisements according to changes in the user's health condition. For example, for a user who has increased the amount of exercise, the advertisement generation unit generates advertisements for sporting events and activities. In this way, by generating advertisements according to the user's health condition based on the user's health data, the effectiveness of the advertisements can be increased.

[0033] The advertisement generation unit can collect data from the user's home devices and generate advertisements tailored to the home environment. The advertisement generation unit, for example, analyzes data from smart home devices to understand the user's home environment. For example, it generates advertisements for products and services that support a comfortable life based on room temperature and lighting settings. The advertisement generation unit also generates advertisements tailored to the user's lifestyle based on the usage of home devices. For example, it generates an advertisement for a music streaming service for a user who frequently uses a smart speaker. The advertisement generation unit also monitors data from smart home devices in real time and generates advertisements tailored to changes in the home environment. For example, it generates advertisements for energy-saving products and services for a user whose energy consumption has increased. In this way, the effectiveness of advertisements can be improved by generating advertisements tailored to the home environment based on data from home devices.

[0034] The advertisement generation unit can combine the user's purchase history and location information to generate an advertisement including a special offer for a specific store or area. The advertisement generation unit, for example, analyzes the user's purchase history to generate an advertisement including a special offer for a specific store or area. For example, for a user who has previously purchased products from a specific brand, the advertisement generation unit generates an advertisement including a discount offer for a store of that brand. The advertisement generation unit also combines the purchase history and location information to generate an advertisement including a special offer for the area where the user is currently located. For example, when the user is in a shopping mall, the advertisement generation unit generates an advertisement including a special offer for a store in the mall. The advertisement generation unit also analyzes the user's purchase history and location information in real time to generate an advertisement including a special offer for a specific store or area. For example, when the user is in a specific area, the advertisement generation unit generates an advertisement including a special offer for a store in that area. In this way, by generating an advertisement including a special offer for a specific store or area based on the user's purchase history and location information, the effectiveness of the advertisement can be improved.

[0035] The advertisement generation unit can analyze a user's past ad click history and learn and reflect the characteristics of advertisements with high click rates. The advertisement generation unit, for example, analyzes a user's past ad click history and learns the characteristics of advertisements with high click rates. For example, it identifies that a particular design or message is effective and reflects that in a new advertisement. The advertisement generation unit also identifies patterns of advertisements that are likely to interest users based on the click history and reflects those patterns in a new advertisement. For example, it learns that a particular color or font is effective and applies that to a new advertisement. The advertisement generation unit also analyzes a user's click history in real time and immediately reflects the characteristics of advertisements with high click rates. For example, it incorporates the characteristics of an advertisement that the user recently clicked into a new advertisement. In this way, it is possible to learn the characteristics of advertisements with high click rates based on a user's past ad click history and increase the effectiveness of advertisements.

[0036] The advertisement generation unit can analyze a user's music streaming history and generate advertisements that match the user's musical tastes. The advertisement generation unit, for example, analyzes a user's music streaming history and generates advertisements that match the user's musical tastes. For example, for a user who likes a particular genre of music, the advertisement generation unit advertises events or products related to that genre. The advertisement generation unit also generates advertisements that are likely to interest the user based on the music streaming history. For example, for a user who is a fan of a particular artist, the advertisement generation unit generates advertisements for new songs or concerts by that artist. The advertisement generation unit also analyzes a user's music streaming history in real time and instantly generates advertisements that match the user's musical tastes. For example, the advertisement generation unit generates advertisements for products or services related to songs the user recently listened to. In this way, the effectiveness of advertisements can be increased by generating advertisements that match the user's musical tastes based on the user's music streaming history.

[0037] The advertisement generation unit can analyze a user's reading history and generate advertisements related to books and articles of interest. The advertisement generation unit, for example, analyzes a user's reading history and generates advertisements related to books and articles of interest. For example, for a user who likes books in a particular genre, advertisements for new releases and events related to that genre are generated. The advertisement generation unit also generates advertisements that are likely to interest the user based on the reading history. For example, for a user who is a fan of a particular author, advertisements for new releases and related events by that author are generated. The advertisement generation unit also analyzes a user's reading history in real time and instantly generates advertisements related to books and articles of interest. For example, advertisements for products and services related to articles the user has recently read are generated. In this way, advertisements related to books and articles of interest based on the user's reading history can be generated, thereby increasing the effectiveness of advertising.

[0038] The advertisement display unit can automatically change the display content of the digital signage according to the surrounding environment. For example, the advertisement display unit automatically changes the display content of the digital signage according to the current weather. For example, on a rainy day, advertisements for umbrellas and raincoats are displayed, and on a sunny day, advertisements for outdoor equipment are displayed. The advertisement display unit also changes the display content of the digital signage according to the time of day. For example, advertisements for coffee shops are displayed during the morning rush hour, and advertisements for restaurants are displayed during the evening rush hour. Furthermore, if a specific event is being held, the advertisement display unit displays advertisements related to that event. For example, if a concert is being held, advertisements for concert goods and related products are displayed. In this way, the effectiveness of advertising can be increased by automatically changing the display content of the digital signage according to the surrounding environment.

[0039] The advertisement display unit is equipped with a camera in the digital signage and can adjust the advertisement content by analyzing the viewer's reactions in real time. The advertisement display unit, for example, is equipped with a camera in the digital signage and adjusts the advertisement content by analyzing the viewer's facial expressions and line of sight. For example, advertisements that the viewer is interested in are displayed for a long period of time. The advertisement display unit also analyzes the viewer's reactions in real time and builds a system to evaluate the effectiveness of advertisements. For example, if the viewer smiles, a positive advertisement is displayed. The advertisement display unit also uses a camera to estimate the viewer's age and gender and customizes the advertisement content based on that data. For example, fashion advertisements are displayed to younger generations and health product advertisements are displayed to seniors. In this way, the effectiveness of advertisements can be increased by equipping the digital signage with a camera and adjusting the advertisement content by analyzing the viewer's reactions in real time.

[0040] The advertisement display unit may make the digital signage interactive, allowing users to customize advertisement content by touch or voice. The advertisement display unit may, for example, be equipped with a touch screen on the digital signage, allowing users to customize advertisement content. For example, the advertisement display unit may select a product or service of interest and display detailed information. The advertisement display unit may also be equipped with a voice recognition function, allowing users to customize advertisement content by voice. For example, when a user speaks a specific keyword, advertisements related to the keyword are displayed. The advertisement display unit may also use the interactive digital signage to allow users to customize advertisement content, thereby providing more personalized advertisements. For example, the user may select an advertisement based on their own interests. This may increase the effectiveness of advertisements by making the digital signage interactive and allowing users to customize advertisement content.

[0041] The advertisement display unit can combine AR technology with digital signage to allow users to experience the advertisement content. The advertisement display unit, for example, combines AR technology with digital signage to allow users to experience the advertisement content. For example, when a user holds their smartphone over the digital signage, a character in the advertisement appears in the real world. The advertisement display unit also uses AR technology to make the advertisement content on the digital signage interactive. For example, the advertisement content changes when the user performs a specific action. The advertisement display unit also combines AR technology with digital signage to allow users to experience the advertisement content more realistically. For example, the user can virtually try on the advertised product. In this way, by combining AR technology with digital signage to allow users to experience the advertisement content, the effectiveness of the advertisement can be increased.

[0042] The advertisement generation unit can analyze demographic data for each specific area of ​​a large city and generate advertisements that are optimal for each area. For example, the advertisement generation unit analyzes demographic data for each specific area of ​​a large city and generates advertisements that are optimal for each area. For example, in an area with a large number of young people, it generates advertisements for fashion and entertainment. The advertisement generation unit also generates advertisements that match the interests of residents of a specific area based on the demographic data. For example, in an area with a large number of families, it generates advertisements for products and services aimed at children. The advertisement generation unit also analyzes demographic data for each specific area of ​​a large city in real time and instantly generates advertisements that are optimal for each area. For example, in an area with a large number of tourists, it generates advertisements for tourist attractions and events. In this way, by analyzing demographic data for each specific area of ​​a large city and generating advertisements that are optimal for each area, the effectiveness of advertising can be increased.

[0043] The advertisement generation unit can generate advertisements tailored to event participants in accordance with a specific event. For example, when a specific event is held, the advertisement generation unit generates advertisements tailored to event participants. For example, when a concert is held, the advertisement generation unit generates advertisements for concert goods and related products. The advertisement generation unit also generates specialized advertisements based on the interests and concerns of event participants. For example, when a sporting event is held, the advertisement generation unit generates advertisements for sporting goods and related services. The advertisement generation unit also generates advertisements tailored to event participants in real time in accordance with a specific event. For example, the advertisement generation unit generates advertisements including special offers and discount information around the event venue. In this way, by generating advertisements tailored to event participants in accordance with a specific event, the effectiveness of the advertisements can be increased.

[0044] The advertisement generation unit can analyze traffic data of a large city and generate advertisements that are optimal for areas with heavy traffic. The advertisement generation unit, for example, analyzes traffic data of a large city and generates advertisements that are optimal for areas with heavy traffic. For example, in areas with heavy traffic during rush hour, advertisements for products and services aimed at commuters are generated. The advertisement generation unit also generates advertisements based on traffic data according to the traffic conditions in a specific area. For example, in areas prone to traffic congestion, advertisements for products and services that allow users to make effective use of waiting time are generated. The advertisement generation unit also analyzes traffic data of a large city in real time and instantly generates advertisements that are optimal for areas with heavy traffic. For example, advertisements that include special offers and discount information for areas with heavy traffic are generated. In this way, the effectiveness of advertising can be increased by analyzing traffic data of a large city and generating advertisements that are optimal for areas with heavy traffic.

[0045] The advertisement generation unit can analyze tourism data of a large city and generate advertisements tailored to tourists. The advertisement generation unit, for example, analyzes tourism data of a large city and generates advertisements tailored to tourists. For example, it generates advertisements for tourist spots and events to appeal to tourists. The advertisement generation unit also generates advertisements tailored to tourists' interests based on the tourism data. For example, it generates advertisements for products and services related to specific tourist spots. The advertisement generation unit also analyzes tourism data of a large city in real time and instantly generates advertisements tailored to tourists. For example, it generates advertisements that include special offers and discount information in areas with many tourists. In this way, by analyzing tourism data of a large city and generating advertisements tailored to tourists, the effectiveness of the advertisements can be increased.

[0046] The advertisement generation unit tracks user behavior after the advertisement is displayed, evaluates the effectiveness of the advertisement in real time, and reflects this in the generation of the next advertisement. The advertisement generation unit, for example, builds a system that tracks user behavior after the advertisement is displayed and evaluates the effectiveness of the advertisement in real time. For example, it analyzes the click rate and purchase rate after viewing the advertisement. The advertisement generation unit also evaluates the effectiveness of the advertisement based on user behavior data and reflects this in the generation of the next advertisement. For example, if a particular advertisement shows high effectiveness, elements of that advertisement are incorporated into the next advertisement. The advertisement generation unit also monitors user behavior in real time after the advertisement is displayed and immediately evaluates the effectiveness of the advertisement. For example, it analyzes the user's movement history and purchase history after viewing the advertisement. In this way, the effectiveness of the advertisement can be improved by tracking user behavior after the advertisement is displayed, evaluating the effectiveness of the advertisement in real time, and reflecting this in the generation of the next advertisement.

[0047] The advertisement generation unit can analyze the advertisement display frequency and user response, and automatically adjust the optimal display frequency. The advertisement generation unit, for example, analyzes the advertisement display frequency and user response, and builds a system that automatically adjusts the optimal display frequency. For example, it analyzes the relationship between the number of times an advertisement is displayed and the click-through rate. The advertisement generation unit also adjusts the advertisement display frequency based on user response data. For example, if a particular advertisement shows a high response, it increases the display frequency of that advertisement. The advertisement generation unit also monitors the advertisement display frequency and user response in real time, and immediately adjusts the optimal display frequency. For example, if the advertisement is displayed too many times, it reduces the display frequency. In this way, the effectiveness of the advertisement can be increased by analyzing the advertisement display frequency and user response, and automatically adjusting the optimal display frequency.

[0048] The advertisement generation unit can compare the effectiveness of advertisements on different devices and deliver advertisements to the optimal device. The advertisement generation unit, for example, builds a system that compares the effectiveness of advertisements on different devices and delivers advertisements to the optimal device. For example, it compares the click rate on smartphones with the click rate on PCs. The advertisement generation unit also analyzes the advertisement effectiveness for each device and delivers advertisements to the optimal device. For example, if a specific advertisement shows high effectiveness on smartphones, it delivers that advertisement preferentially to smartphones. The advertisement generation unit also monitors the effectiveness of advertisements in real time and delivers advertisements to the optimal device immediately. For example, it analyzes user behavior after an advertisement is displayed and identifies the optimal device. This allows the effectiveness of advertisements to be compared on different devices and delivered to the optimal device, thereby increasing the effectiveness of advertisements.

[0049] The advertisement generation unit can compare the effectiveness of advertisements at different time periods and days of the week and deliver advertisements at the optimal timing. The advertisement generation unit, for example, compares the effectiveness of advertisements at different time periods and days of the week and builds a system that delivers advertisements at the optimal timing. For example, it compares the click rates during weekday daytime hours and weekend nights. The advertisement generation unit also analyzes the advertisement effectiveness for each time period and day of the week and delivers advertisements at the optimal timing. For example, if a particular advertisement shows high effectiveness on weekend nights, it delivers that advertisement preferentially on weekend nights. The advertisement generation unit also monitors the advertisement effectiveness in real time and delivers advertisements immediately at the optimal timing. For example, it analyzes user behavior after an advertisement is displayed and identifies the optimal time period and day of the week. This makes it possible to compare the advertisement effectiveness at different time periods and days of the week and deliver advertisements at the optimal timing, thereby increasing the advertisement effectiveness.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The advertisement generation system can further analyze a user's music streaming history to generate advertisements that match the user's musical tastes. For example, for a user who likes a particular genre of music, the advertisement generation unit can advertise events or products related to that genre. The advertisement generation unit also generates advertisements that are likely to interest the user based on the music streaming history. For example, for a user who is a fan of a particular artist, the advertisement generation unit can generate advertisements for the artist's new songs or concerts. The advertisement generation unit also analyzes the user's music streaming history in real time to instantly generate advertisements that match the user's musical tastes. For example, the advertisement generation unit can generate advertisements for products or services related to songs the user recently listened to. This can increase the effectiveness of advertisements by generating advertisements that match the user's musical tastes based on the user's music streaming history.

[0052] The advertisement generation system can further analyze a user's reading history and generate advertisements related to books and articles of interest. For example, for a user who likes books in a particular genre, advertisements for new releases and events related to that genre are generated. The advertisement generation unit also generates advertisements that are likely to interest the user based on the reading history. For example, for a user who is a fan of a particular author, advertisements for new releases and related events by that author are generated. The advertisement generation unit also analyzes the user's reading history in real time and instantly generates advertisements related to books and articles of interest. For example, advertisements for products and services related to articles the user has recently read are generated. In this way, the effectiveness of advertisements can be increased by generating advertisements related to books and articles of interest based on the user's reading history.

[0053] The advertisement generation system can further collect data from the user's home devices and generate advertisements tailored to the home environment. For example, the system analyzes data from smart home devices to understand the user's home environment. For example, it generates advertisements for products and services that support a comfortable life based on room temperature and lighting settings. The advertisement generation unit also generates advertisements tailored to the user's lifestyle based on the usage of the home devices. For example, it generates advertisements for music streaming services for users who frequently use smart speakers. The advertisement generation unit also monitors data from smart home devices in real time and generates advertisements tailored to changes in the home environment. For example, it generates advertisements for energy-saving products and services for users whose energy consumption has increased. This allows the effectiveness of advertisements to be improved by generating advertisements tailored to the home environment based on data from home devices.

[0054] The advertisement generation system can further collect user health data and generate advertisements tailored to the user's health condition. For example, data from a fitness tracker can be analyzed to understand the user's exercise habits and health condition. For example, advertisements for sports equipment and fitness gyms can be generated for a user who exercises regularly. The advertisement generation unit can also generate advertisements tailored to the user's health condition based on the health data. For example, advertisements for sleep aids and relaxation services can be generated for a user who is sleep-deprived. The advertisement generation unit can also monitor the user's health data in real time and generate advertisements tailored to changes in the user's health condition. For example, advertisements for sporting events and activities can be generated for a user who has increased their exercise volume. This can increase the effectiveness of advertisements by generating advertisements tailored to the user's health condition based on the user's health data.

[0055] The advertisement generation system can further analyze a user's past ad click history and learn and reflect the characteristics of advertisements with high click rates. For example, the advertisement generation system can analyze a user's past ad click history and learn the characteristics of advertisements with high click rates. For example, it can identify that a particular design or message is effective and reflect that in a new advertisement. The advertisement generation unit can also identify patterns of advertisements that are likely to interest users based on the click history and reflect those patterns in a new advertisement. For example, it can learn that a particular color or font is effective and apply that to a new advertisement. The advertisement generation unit can also analyze a user's click history in real time and immediately reflect the characteristics of advertisements with high click rates. For example, it can incorporate the characteristics of an advertisement that the user recently clicked in a new advertisement. In this way, it can learn the characteristics of advertisements with high click rates based on a user's past ad click history and improve the effectiveness of advertisements.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The personal information collection department collects personal information, such as the user's name, age, gender, contact information, information about interests, purchase history, and information based on social media activity. Step 2: The location information collection unit collects location information, such as GPS data, Wi-Fi location information, and beacon data. Step 3: The advertisement generation unit generates advertisements based on the personal information and location information collected by the personal information collection unit and location information collection unit. For example, it generates personalized advertisements using a generation AI and customizes advertisements based on the user's interests and current location. Step 4: The advertisement display unit displays the advertisement generated by the advertisement generation unit on digital signage. For example, the advertisement is displayed on digital signage installed around town or in a specific area, and the advertisement is updated in real time.

[0058] (Example 2) The advertisement generation system according to an embodiment of the present invention is a system that generates personalized advertisements in real time not only for online advertisements but also for digital signage around town by having a generation AI learn the personal information and location information of Yahoo! JAPAN IDs. This allows the advertisement generation system to generate personalized advertisements in real time based on personal information and location information and display them on digital signage.

[0059] An advertisement generation system according to an embodiment includes a personal information collection unit, a location information collection unit, an advertisement generation unit, and an advertisement display unit. The personal information collection unit collects personal information. For example, the personal information collection unit collects a user's name, age, gender, and contact information. The personal information collection unit may also collect information related to the user's interests. The personal information collection unit may also collect information based on the user's purchase history and social media activity. The location information collection unit collects location information. For example, the location information collection unit collects GPS data. The location information collection unit may also collect Wi-Fi location information. The location information collection unit may also collect beacon data. The advertisement generation unit generates an advertisement based on the personal information and location information collected by the personal information collection unit and the location information collection unit. For example, the advertisement generation unit generates a personalized advertisement based on the user's personal information and location information using a generation AI. The advertisement generation unit may also customize the advertisement based on the user's interests. The advertisement generation unit may also generate an advertisement based on the user's current location. The advertisement display unit displays the advertisement generated by the advertisement generation unit on a digital signage. For example, the advertisement display unit displays advertisements on digital signage throughout the city. The advertisement display unit can also display advertisements on digital signage installed in specific areas or locations. The advertisement display unit can also update and display advertisements in real time. This allows the advertisement generation system to generate personalized advertisements based on personal information and location information in real time and display them on digital signage.

[0060] The advertisement generation unit can combine a user's past movement history and purchase history to predict future behavior and generate advertisements based on that prediction. The advertisement generation unit, for example, analyzes a user's past movement history and finds specific patterns. For example, for a user who visits a specific shopping mall every weekend, it generates advertisements for stores in that mall. The advertisement generation unit also analyzes a user's purchase history and generates relevant advertisements based on products and services purchased in the past. For example, for a user who has previously purchased sporting goods, it generates an advertisement for a new sporting event. The advertisement generation unit also combines the movement history and purchase history to predict a user's future behavior and generate advertisements based on that prediction. For example, for a user who is likely to participate in an event in a specific area, it generates an advertisement for that event. This makes it possible to predict future behavior based on a user's past behavior data and generate more effective advertisements.

[0061] The ad generation unit analyzes a user's social media activity and can reflect changes in interests in real time. For example, the ad generation unit analyzes a user's social media posts to detect changes in interests. For example, if a user has started to take up a new hobby or interest, the ad generation unit generates an ad related to that hobby. The ad generation unit also analyzes a user's following and like history on social media to identify trends in interests. For example, if a user shows increasing interest in a particular brand or product, the ad generation unit generates an ad for that brand. The ad generation unit also monitors a user's social media activity in real time and immediately reflects changes in interests. For example, if a user shows interest in a new event or campaign, the ad generation unit generates an ad for that event. This allows changes in interests to be reflected in real time based on the user's social media activity, thereby improving the effectiveness of advertising.

[0062] The advertisement generation unit can use the emotion estimation function to analyze the user's current emotional state and generate an advertisement that matches that emotion. The advertisement generation unit, for example, analyzes the user's facial expression or voice to estimate the user's current emotional state. For example, if the user is relaxed, the advertisement generation unit generates an advertisement for a product or service that will help them relax. Furthermore, the advertisement generation unit uses the emotion estimation function to generate an advertisement for a product or service that will help relieve stress if the user is feeling stressed. For example, the advertisement generation unit generates an advertisement for a relaxation facility or massage. Furthermore, the advertisement generation unit monitors the user's emotional state in real time and generates an advertisement that matches that emotion. For example, if the user is excited, the advertisement generation unit generates an advertisement for entertainment or activities. In this way, the effectiveness of the advertisement can be increased by analyzing the user's emotional state and generating an advertisement that matches that emotion.

[0063] The advertisement generation unit can collect health data of a user and generate advertisements according to the user's health condition. The advertisement generation unit, for example, analyzes data from a fitness tracker to understand the user's exercise habits and health condition. For example, for a user who exercises regularly, the advertisement generation unit generates advertisements for sports equipment and fitness gyms. The advertisement generation unit also generates advertisements according to the user's health condition based on the health data. For example, for a user who is sleep-deprived, the advertisement generation unit generates advertisements for sleep aids and relaxation services. The advertisement generation unit also monitors the user's health data in real time and generates advertisements according to changes in the user's health condition. For example, for a user who has increased the amount of exercise, the advertisement generation unit generates advertisements for sporting events and activities. In this way, by generating advertisements according to the user's health condition based on the user's health data, the effectiveness of the advertisements can be increased.

[0064] The advertisement generation unit can collect data from the user's home devices and generate advertisements tailored to the home environment. The advertisement generation unit, for example, analyzes data from smart home devices to understand the user's home environment. For example, it generates advertisements for products and services that support a comfortable life based on room temperature and lighting settings. The advertisement generation unit also generates advertisements tailored to the user's lifestyle based on the usage of home devices. For example, it generates an advertisement for a music streaming service for a user who frequently uses a smart speaker. The advertisement generation unit also monitors data from smart home devices in real time and generates advertisements tailored to changes in the home environment. For example, it generates advertisements for energy-saving products and services for a user whose energy consumption has increased. In this way, the effectiveness of advertisements can be improved by generating advertisements tailored to the home environment based on data from home devices.

[0065] The advertisement generation unit can use the emotion estimation function to analyze the emotions of a user when they are in a specific location and generate an advertisement appropriate for that location. The advertisement generation unit, for example, analyzes the emotions of a user when they are in a specific location and generates an advertisement appropriate for that location. For example, if a user is relaxing in a cafe, the advertisement generation unit generates an advertisement for a product or service that helps them relax. Furthermore, the advertisement generation unit uses the emotion estimation function to generate an advertisement for a product or service that helps relieve stress when a user is feeling stressed in a specific location. For example, the advertisement generation unit generates an advertisement for a relaxation facility or a massage. Furthermore, the advertisement generation unit monitors the user's emotional state in real time and generates an advertisement appropriate for that location. For example, if a user is excited in a shopping mall, the advertisement generation unit generates an advertisement for entertainment or activities. In this way, the effectiveness of the advertisement can be improved by analyzing the emotions of a user when they are in a specific location and generating an advertisement appropriate for that location.

[0066] The advertisement generation unit can combine the user's purchase history and location information to generate an advertisement including a special offer for a specific store or area. The advertisement generation unit, for example, analyzes the user's purchase history to generate an advertisement including a special offer for a specific store or area. For example, for a user who has previously purchased products from a specific brand, the advertisement generation unit generates an advertisement including a discount offer for a store of that brand. The advertisement generation unit also combines the purchase history and location information to generate an advertisement including a special offer for the area where the user is currently located. For example, when the user is in a shopping mall, the advertisement generation unit generates an advertisement including a special offer for a store in the mall. The advertisement generation unit also analyzes the user's purchase history and location information in real time to generate an advertisement including a special offer for a specific store or area. For example, when the user is in a specific area, the advertisement generation unit generates an advertisement including a special offer for a store in that area. In this way, by generating an advertisement including a special offer for a specific store or area based on the user's purchase history and location information, the effectiveness of the advertisement can be improved.

[0067] The advertisement generation unit can analyze a user's past ad click history and learn and reflect the characteristics of advertisements with high click rates. The advertisement generation unit, for example, analyzes a user's past ad click history and learns the characteristics of advertisements with high click rates. For example, it identifies that a particular design or message is effective and reflects that in a new advertisement. The advertisement generation unit also identifies patterns of advertisements that are likely to interest users based on the click history and reflects those patterns in a new advertisement. For example, it learns that a particular color or font is effective and applies that to a new advertisement. The advertisement generation unit also analyzes a user's click history in real time and immediately reflects the characteristics of advertisements with high click rates. For example, it incorporates the characteristics of an advertisement that the user recently clicked into a new advertisement. In this way, it is possible to learn the characteristics of advertisements with high click rates based on a user's past ad click history and increase the effectiveness of advertisements.

[0068] The advertisement generation unit can customize the color and design of an advertisement based on the user's emotion using the emotion estimation function. The advertisement generation unit, for example, uses the emotion estimation function to customize the color and design of an advertisement based on the user's emotion. For example, if the user is relaxed, the advertisement is generated with a calming color and design. The advertisement generation unit also analyzes the user's emotional state in real time and generates an advertisement with a color and design that matches the emotion. For example, if the user is excited, the advertisement is generated with a vivid color and a dynamic design. The advertisement generation unit also selects the color and design of an advertisement that is optimal for the user's emotion based on the emotion estimation data. For example, if the user is feeling stressed, the advertisement is generated with a relaxing color and design. In this way, by customizing the color and design of an advertisement based on the user's emotion, the effectiveness of the advertisement can be improved.

[0069] The advertisement generation unit can analyze a user's music streaming history and generate advertisements that match the user's musical tastes. The advertisement generation unit, for example, analyzes a user's music streaming history and generates advertisements that match the user's musical tastes. For example, for a user who likes a particular genre of music, the advertisement generation unit advertises events or products related to that genre. The advertisement generation unit also generates advertisements that are likely to interest the user based on the music streaming history. For example, for a user who is a fan of a particular artist, the advertisement generation unit generates advertisements for new songs or concerts by that artist. The advertisement generation unit also analyzes a user's music streaming history in real time and instantly generates advertisements that match the user's musical tastes. For example, the advertisement generation unit generates advertisements for products or services related to songs the user recently listened to. In this way, the effectiveness of advertisements can be increased by generating advertisements that match the user's musical tastes based on the user's music streaming history.

[0070] The advertisement generation unit can analyze a user's reading history and generate advertisements related to books and articles of interest. The advertisement generation unit, for example, analyzes a user's reading history and generates advertisements related to books and articles of interest. For example, for a user who likes books in a particular genre, advertisements for new releases and events related to that genre are generated. The advertisement generation unit also generates advertisements that are likely to interest the user based on the reading history. For example, for a user who is a fan of a particular author, advertisements for new releases and related events by that author are generated. The advertisement generation unit also analyzes a user's reading history in real time and instantly generates advertisements related to books and articles of interest. For example, advertisements for products and services related to articles the user has recently read are generated. In this way, advertisements related to books and articles of interest based on the user's reading history can be generated, thereby increasing the effectiveness of advertising.

[0071] The advertisement generation unit can use the emotion estimation function to analyze the emotion of a user when listening to specific music and generate an advertisement that matches that emotion. For example, the advertisement generation unit uses the emotion estimation function to analyze the emotion of a user when listening to specific music and generate an advertisement that matches that emotion. For example, if the user is relaxed, the advertisement generation unit generates an advertisement for a product or service that helps relaxation. The advertisement generation unit also analyzes the emotional state of the user in real time and generates an advertisement that matches that emotion. For example, if the user is excited, the advertisement generation unit generates an advertisement for entertainment or activities. The advertisement generation unit also selects an advertisement that is optimal for the emotion of the user when listening to specific music based on the emotion estimation data. For example, if the user is feeling stressed, the advertisement generation unit generates an advertisement for a relaxation facility or massage. In this way, by analyzing the emotion of a user when listening to specific music and generating an advertisement that matches that emotion, the effectiveness of the advertisement can be increased.

[0072] The advertisement display unit can automatically change the display content of the digital signage according to the surrounding environment. For example, the advertisement display unit automatically changes the display content of the digital signage according to the current weather. For example, on a rainy day, advertisements for umbrellas and raincoats are displayed, and on a sunny day, advertisements for outdoor equipment are displayed. The advertisement display unit also changes the display content of the digital signage according to the time of day. For example, advertisements for coffee shops are displayed during the morning rush hour, and advertisements for restaurants are displayed during the evening rush hour. Furthermore, if a specific event is being held, the advertisement display unit displays advertisements related to that event. For example, if a concert is being held, advertisements for concert goods and related products are displayed. In this way, the effectiveness of advertising can be increased by automatically changing the display content of the digital signage according to the surrounding environment.

[0073] The advertisement display unit is equipped with a camera in the digital signage and can adjust the advertisement content by analyzing the viewer's reactions in real time. The advertisement display unit, for example, is equipped with a camera in the digital signage and adjusts the advertisement content by analyzing the viewer's facial expressions and line of sight. For example, advertisements that the viewer is interested in are displayed for a long period of time. The advertisement display unit also analyzes the viewer's reactions in real time and builds a system to evaluate the effectiveness of advertisements. For example, if the viewer smiles, a positive advertisement is displayed. The advertisement display unit also uses a camera to estimate the viewer's age and gender and customizes the advertisement content based on that data. For example, fashion advertisements are displayed to younger generations and health product advertisements are displayed to seniors. In this way, the effectiveness of advertisements can be increased by equipping the digital signage with a camera and adjusting the advertisement content by analyzing the viewer's reactions in real time.

[0074] The advertisement display unit can use the emotion estimation function to analyze the emotions of people in front of the digital signage and display advertisements that match those emotions. For example, the advertisement display unit uses the emotion estimation function to analyze the emotions of people in front of the digital signage and display advertisements that match those emotions. For example, advertisements for relaxation products and services are displayed to people who are relaxed. The advertisement display unit also analyzes the emotional state of people in front of the digital signage in real time and instantly displays advertisements that match those emotions. For example, advertisements for entertainment and activities are displayed to people who are excited. The advertisement display unit also selects advertisements that are optimal for the emotions of people in front of the digital signage based on the emotion estimation data. For example, advertisements for relaxation facilities and massages are displayed to people who are feeling stressed. In this way, the effectiveness of advertisements can be increased by analyzing the emotions of people in front of the digital signage and displaying advertisements that match those emotions.

[0075] The advertisement display unit may make the digital signage interactive, allowing users to customize advertisement content by touch or voice. The advertisement display unit may, for example, be equipped with a touch screen on the digital signage, allowing users to customize advertisement content. For example, the advertisement display unit may select a product or service of interest and display detailed information. The advertisement display unit may also be equipped with a voice recognition function, allowing users to customize advertisement content by voice. For example, when a user speaks a specific keyword, advertisements related to the keyword are displayed. The advertisement display unit may also use the interactive digital signage to allow users to customize advertisement content, thereby providing more personalized advertisements. For example, the user may select an advertisement based on their own interests. This may increase the effectiveness of advertisements by making the digital signage interactive and allowing users to customize advertisement content.

[0076] The advertisement display unit can combine AR technology with digital signage to allow users to experience the advertisement content. The advertisement display unit, for example, combines AR technology with digital signage to allow users to experience the advertisement content. For example, when a user holds their smartphone over the digital signage, a character in the advertisement appears in the real world. The advertisement display unit also uses AR technology to make the advertisement content on the digital signage interactive. For example, the advertisement content changes when the user performs a specific action. The advertisement display unit also combines AR technology with digital signage to allow users to experience the advertisement content more realistically. For example, the user can virtually try on the advertised product. In this way, by combining AR technology with digital signage to allow users to experience the advertisement content, the effectiveness of the advertisement can be increased.

[0077] The advertisement display unit can use the emotion estimation function to analyze the emotions of people in front of the digital signage and provide interactive content that matches those emotions. For example, the advertisement display unit can use the emotion estimation function to analyze the emotions of people in front of the digital signage and provide interactive content that matches those emotions. For example, relaxation games and quizzes can be provided to people who are relaxed. The advertisement display unit can also analyze the emotional states of people in front of the digital signage in real time and instantly provide interactive content that matches those emotions. For example, entertainment and activity content can be provided to people who are excited. The advertisement display unit can also select interactive content that best suits the emotions of people in front of the digital signage based on the emotion estimation data. For example, relaxation games and quizzes can be provided to people who are feeling stressed. In this way, the effectiveness of advertising can be increased by analyzing the emotions of people in front of the digital signage and providing interactive content that matches those emotions.

[0078] The advertisement generation unit can analyze demographic data for each specific area of ​​a large city and generate advertisements that are optimal for each area. For example, the advertisement generation unit analyzes demographic data for each specific area of ​​a large city and generates advertisements that are optimal for each area. For example, in an area with a large number of young people, it generates advertisements for fashion and entertainment. The advertisement generation unit also generates advertisements that match the interests of residents of a specific area based on the demographic data. For example, in an area with a large number of families, it generates advertisements for products and services aimed at children. The advertisement generation unit also analyzes demographic data for each specific area of ​​a large city in real time and instantly generates advertisements that are optimal for each area. For example, in an area with a large number of tourists, it generates advertisements for tourist attractions and events. In this way, by analyzing demographic data for each specific area of ​​a large city and generating advertisements that are optimal for each area, the effectiveness of advertising can be increased.

[0079] The advertisement generation unit can generate advertisements tailored to event participants in accordance with a specific event. For example, when a specific event is held, the advertisement generation unit generates advertisements tailored to event participants. For example, when a concert is held, the advertisement generation unit generates advertisements for concert goods and related products. The advertisement generation unit also generates specialized advertisements based on the interests and concerns of event participants. For example, when a sporting event is held, the advertisement generation unit generates advertisements for sporting goods and related services. The advertisement generation unit also generates advertisements tailored to event participants in real time in accordance with a specific event. For example, the advertisement generation unit generates advertisements including special offers and discount information around the event venue. In this way, by generating advertisements tailored to event participants in accordance with a specific event, the effectiveness of the advertisements can be increased.

[0080] The advertisement generation unit can use the emotion estimation function to analyze the emotions of people in a specific area of ​​a large city and generate advertisements that match those emotions. For example, the advertisement generation unit uses the emotion estimation function to analyze the emotions of people in a specific area of ​​a large city and generate advertisements that match those emotions. For example, it generates advertisements for relaxation products and services for people who are relaxed. The advertisement generation unit also analyzes the emotional state of people in a specific area in real time and instantly generates advertisements that match those emotions. For example, it generates advertisements for entertainment and activities for people who are excited. The advertisement generation unit also selects advertisements that are optimal for the emotions of people in a specific area of ​​a large city based on the emotion estimation data. For example, it generates advertisements for relaxation facilities and massages for people who are feeling stressed. In this way, the effectiveness of advertisements can be increased by analyzing the emotions of people in a specific area of ​​a large city and generating advertisements that match those emotions.

[0081] The advertisement generation unit can analyze traffic data of a large city and generate advertisements that are optimal for areas with heavy traffic. The advertisement generation unit, for example, analyzes traffic data of a large city and generates advertisements that are optimal for areas with heavy traffic. For example, in areas with heavy traffic during rush hour, advertisements for products and services aimed at commuters are generated. The advertisement generation unit also generates advertisements based on traffic data according to the traffic conditions in a specific area. For example, in areas prone to traffic congestion, advertisements for products and services that allow users to make effective use of waiting time are generated. The advertisement generation unit also analyzes traffic data of a large city in real time and instantly generates advertisements that are optimal for areas with heavy traffic. For example, advertisements that include special offers and discount information for areas with heavy traffic are generated. In this way, the effectiveness of advertising can be increased by analyzing traffic data of a large city and generating advertisements that are optimal for areas with heavy traffic.

[0082] The advertisement generation unit can analyze tourism data of a large city and generate advertisements tailored to tourists. The advertisement generation unit, for example, analyzes tourism data of a large city and generates advertisements tailored to tourists. For example, it generates advertisements for tourist spots and events to appeal to tourists. The advertisement generation unit also generates advertisements tailored to tourists' interests based on the tourism data. For example, it generates advertisements for products and services related to specific tourist spots. The advertisement generation unit also analyzes tourism data of a large city in real time and instantly generates advertisements tailored to tourists. For example, it generates advertisements that include special offers and discount information in areas with many tourists. In this way, by analyzing tourism data of a large city and generating advertisements tailored to tourists, the effectiveness of the advertisements can be increased.

[0083] The advertisement generation unit can use the emotion estimation function to analyze the emotions of tourists in a specific area of ​​a large city and generate advertisements that match those emotions. For example, the advertisement generation unit uses the emotion estimation function to analyze the emotions of tourists in a specific area of ​​a large city and generate advertisements that match those emotions. For example, for tourists who are relaxed, it generates advertisements for relaxation products and services. The advertisement generation unit also analyzes the emotional state of tourists in a specific area in real time and instantly generates advertisements that match those emotions. For example, for tourists who are excited, it generates advertisements for entertainment and activities. The advertisement generation unit also selects advertisements that are optimal for the emotions of tourists in a specific area of ​​a large city based on the emotion estimation data. For example, for tourists who are feeling stressed, it generates advertisements for relaxation facilities and massages. In this way, by analyzing the emotions of tourists in a specific area of ​​a large city and generating advertisements that match those emotions, the effectiveness of the advertisements can be increased.

[0084] The advertisement generation unit tracks user behavior after the advertisement is displayed, evaluates the effectiveness of the advertisement in real time, and reflects this in the generation of the next advertisement. The advertisement generation unit, for example, builds a system that tracks user behavior after the advertisement is displayed and evaluates the effectiveness of the advertisement in real time. For example, it analyzes the click rate and purchase rate after viewing the advertisement. The advertisement generation unit also evaluates the effectiveness of the advertisement based on user behavior data and reflects this in the generation of the next advertisement. For example, if a particular advertisement shows high effectiveness, elements of that advertisement are incorporated into the next advertisement. The advertisement generation unit also monitors user behavior in real time after the advertisement is displayed and immediately evaluates the effectiveness of the advertisement. For example, it analyzes the user's movement history and purchase history after viewing the advertisement. In this way, the effectiveness of the advertisement can be improved by tracking user behavior after the advertisement is displayed, evaluating the effectiveness of the advertisement in real time, and reflecting this in the generation of the next advertisement.

[0085] The advertisement generation unit can analyze the advertisement display frequency and user response, and automatically adjust the optimal display frequency. The advertisement generation unit, for example, analyzes the advertisement display frequency and user response, and builds a system that automatically adjusts the optimal display frequency. For example, it analyzes the relationship between the number of times an advertisement is displayed and the click-through rate. The advertisement generation unit also adjusts the advertisement display frequency based on user response data. For example, if a particular advertisement shows a high response, it increases the display frequency of that advertisement. The advertisement generation unit also monitors the advertisement display frequency and user response in real time, and immediately adjusts the optimal display frequency. For example, if the advertisement is displayed too many times, it reduces the display frequency. In this way, the effectiveness of the advertisement can be increased by analyzing the advertisement display frequency and user response, and automatically adjusting the optimal display frequency.

[0086] The advertisement generation unit can use the emotion estimation function to analyze the user's emotion after viewing the advertisement and generate an advertisement that elicits a positive emotional response. The advertisement generation unit, for example, uses the emotion estimation function to analyze the user's emotion after viewing the advertisement and generate an advertisement that elicits a positive emotional response. For example, if the user smiles, the advertisement generation unit generates an advertisement that includes a positive message. The advertisement generation unit also analyzes the user's emotional state after viewing the advertisement in real time and instantly generates an advertisement that elicits a positive emotional response. For example, if the user is excited, the advertisement generation unit generates an advertisement for entertainment or activities. The advertisement generation unit also selects an advertisement that best suits the user's emotion after viewing the advertisement based on the emotion estimation data. For example, if the user is relaxed, the advertisement generation unit generates an advertisement for relaxation products or services. In this way, the effectiveness of the advertisement can be improved by analyzing the user's emotion after viewing the advertisement and generating an advertisement that elicits a positive emotional response.

[0087] The advertisement generation unit can compare the effectiveness of advertisements on different devices and deliver advertisements to the optimal device. The advertisement generation unit, for example, builds a system that compares the effectiveness of advertisements on different devices and delivers advertisements to the optimal device. For example, it compares the click rate on smartphones with the click rate on PCs. The advertisement generation unit also analyzes the advertisement effectiveness for each device and delivers advertisements to the optimal device. For example, if a specific advertisement shows high effectiveness on smartphones, it delivers that advertisement preferentially to smartphones. The advertisement generation unit also monitors the effectiveness of advertisements in real time and delivers advertisements to the optimal device immediately. For example, it analyzes user behavior after an advertisement is displayed and identifies the optimal device. This allows the effectiveness of advertisements to be compared on different devices and delivered to the optimal device, thereby increasing the effectiveness of advertisements.

[0088] The advertisement generation unit can compare the effectiveness of advertisements at different time periods and days of the week and deliver advertisements at the optimal timing. The advertisement generation unit, for example, compares the effectiveness of advertisements at different time periods and days of the week and builds a system that delivers advertisements at the optimal timing. For example, it compares the click rates during weekday daytime hours and weekend nights. The advertisement generation unit also analyzes the advertisement effectiveness for each time period and day of the week and delivers advertisements at the optimal timing. For example, if a particular advertisement shows high effectiveness on weekend nights, it delivers that advertisement preferentially on weekend nights. The advertisement generation unit also monitors the advertisement effectiveness in real time and delivers advertisements immediately at the optimal timing. For example, it analyzes user behavior after an advertisement is displayed and identifies the optimal time period and day of the week. This makes it possible to compare the advertisement effectiveness at different time periods and days of the week and deliver advertisements at the optimal timing, thereby increasing the advertisement effectiveness.

[0089] The advertisement generation unit can use the emotion estimation function to analyze the user's emotion after viewing the advertisement and identify the timing to elicit a positive emotional response. The advertisement generation unit, for example, uses the emotion estimation function to analyze the user's emotion after viewing the advertisement and identify the timing to elicit a positive emotional response. For example, the advertisement is delivered during a time period when the user is relaxed. The advertisement generation unit also analyzes the user's emotional state after viewing the advertisement in real time and immediately identifies the timing to elicit a positive emotional response. For example, the advertisement is delivered during a time period when the user is excited. The advertisement generation unit also selects the optimal timing for the user's emotion after viewing the advertisement based on the emotion estimation data. For example, the advertisement is delivered during a time period when the user is not feeling stressed. In this way, the effectiveness of the advertisement can be improved by analyzing the user's emotion after viewing the advertisement and identifying the timing to elicit a positive emotional response.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The advertisement generation system can further analyze a user's music streaming history to generate advertisements that match the user's musical tastes. For example, for a user who likes a particular genre of music, the advertisement generation unit can advertise events or products related to that genre. The advertisement generation unit also generates advertisements that are likely to interest the user based on the music streaming history. For example, for a user who is a fan of a particular artist, the advertisement generation unit can generate advertisements for the artist's new songs or concerts. The advertisement generation unit also analyzes the user's music streaming history in real time to instantly generate advertisements that match the user's musical tastes. For example, the advertisement generation unit can generate advertisements for products or services related to songs the user recently listened to. This can increase the effectiveness of advertisements by generating advertisements that match the user's musical tastes based on the user's music streaming history.

[0092] The advertisement generation system can further analyze a user's reading history and generate advertisements related to books and articles of interest. For example, for a user who likes books in a particular genre, advertisements for new releases and events related to that genre are generated. The advertisement generation unit also generates advertisements that are likely to interest the user based on the reading history. For example, for a user who is a fan of a particular author, advertisements for new releases and related events by that author are generated. The advertisement generation unit also analyzes the user's reading history in real time and instantly generates advertisements related to books and articles of interest. For example, advertisements for products and services related to articles the user has recently read are generated. In this way, the effectiveness of advertisements can be increased by generating advertisements related to books and articles of interest based on the user's reading history.

[0093] The advertisement generation system can further collect data from the user's home devices and generate advertisements tailored to the home environment. For example, the system analyzes data from smart home devices to understand the user's home environment. For example, it generates advertisements for products and services that support a comfortable life based on room temperature and lighting settings. The advertisement generation unit also generates advertisements tailored to the user's lifestyle based on the usage of the home devices. For example, it generates advertisements for music streaming services for users who frequently use smart speakers. The advertisement generation unit also monitors data from smart home devices in real time and generates advertisements tailored to changes in the home environment. For example, it generates advertisements for energy-saving products and services for users whose energy consumption has increased. This allows the effectiveness of advertisements to be improved by generating advertisements tailored to the home environment based on data from home devices.

[0094] The advertisement generation system can further collect user health data and generate advertisements tailored to the user's health condition. For example, data from a fitness tracker can be analyzed to understand the user's exercise habits and health condition. For example, advertisements for sports equipment and fitness gyms can be generated for a user who exercises regularly. The advertisement generation unit can also generate advertisements tailored to the user's health condition based on the health data. For example, advertisements for sleep aids and relaxation services can be generated for a user who is sleep-deprived. The advertisement generation unit can also monitor the user's health data in real time and generate advertisements tailored to changes in the user's health condition. For example, advertisements for sporting events and activities can be generated for a user who has increased their exercise volume. This can increase the effectiveness of advertisements by generating advertisements tailored to the user's health condition based on the user's health data.

[0095] The advertisement generation system can further analyze a user's past ad click history and learn and reflect the characteristics of advertisements with high click rates. For example, the advertisement generation system can analyze a user's past ad click history and learn the characteristics of advertisements with high click rates. For example, it can identify that a particular design or message is effective and reflect that in a new advertisement. The advertisement generation unit can also identify patterns of advertisements that are likely to interest users based on the click history and reflect those patterns in a new advertisement. For example, it can learn that a particular color or font is effective and apply that to a new advertisement. The advertisement generation unit can also analyze a user's click history in real time and immediately reflect the characteristics of advertisements with high click rates. For example, it can incorporate the characteristics of an advertisement that the user recently clicked in a new advertisement. In this way, it can learn the characteristics of advertisements with high click rates based on a user's past ad click history and improve the effectiveness of advertisements.

[0096] The advertisement generation system can further estimate the user's emotions and customize the color and design of the advertisement based on the estimated user's emotions. For example, if the user is relaxed, the advertisement is generated with calming colors and designs. The advertisement generation unit also analyzes the user's emotional state in real time and generates an advertisement with colors and designs that match the user's emotions. For example, if the user is excited, the advertisement is generated with vivid colors and dynamic designs. The advertisement generation unit also selects the color and design of the advertisement that best suits the user's emotions based on the emotion estimation data. For example, if the user is feeling stressed, the advertisement is generated with relaxing colors and designs. In this way, the effectiveness of the advertisement can be increased by customizing the color and design of the advertisement based on the user's emotions.

[0097] The advertisement generation system can further analyze the emotions of a user when listening to specific music and generate advertisements that match those emotions. For example, the emotion estimation function can be used to analyze the emotions of a user when listening to specific music and generate advertisements that match those emotions. For example, if the user is relaxed, advertisements for products and services that will help them relax are generated. The advertisement generation unit can also analyze the user's emotional state in real time and generate advertisements that match those emotions. For example, if the user is excited, advertisements for entertainment and activities are generated. The advertisement generation unit can also select advertisements that are optimal for the emotions of a user when listening to specific music, based on the emotion estimation data. For example, if the user is feeling stressed, advertisements for relaxation facilities and massages are generated. In this way, the effectiveness of advertisements can be improved by analyzing the emotions of a user when listening to specific music and generating advertisements that match those emotions.

[0098] The advertisement generation system can further analyze the emotions of a user when they are in a specific location and generate an advertisement appropriate for that location. For example, the advertisement generation system analyzes the emotions of a user when they are in a specific location and generates an advertisement appropriate for that location. For example, if a user is relaxing in a cafe, the advertisement generation unit generates an advertisement for products and services that help them relax. Furthermore, if a user is feeling stressed in a specific location, the advertisement generation unit uses the emotion estimation function to generate an advertisement for products and services that help relieve stress. For example, the advertisement generation unit generates an advertisement for relaxation facilities or massages. Furthermore, the advertisement generation unit monitors the user's emotional state in real time and generates an advertisement appropriate for that location. For example, if a user is excited in a shopping mall, the advertisement generation unit generates an advertisement for entertainment or activities. In this way, the effectiveness of advertising can be improved by analyzing the emotions of a user when they are in a specific location and generating an advertisement appropriate for that location.

[0099] The advertisement generation system can further estimate the user's emotions and, based on the estimated user emotions, analyze the user's emotions after viewing the advertisement and generate an advertisement that elicits a positive emotional response. For example, the emotion estimation function is used to analyze the user's emotions after viewing the advertisement and generate an advertisement that elicits a positive emotional response. For example, if the user smiles, an advertisement containing a positive message is generated. The advertisement generation unit also analyzes the user's emotional state after viewing the advertisement in real time and instantly generates an advertisement that elicits a positive emotional response. For example, if the user is excited, an advertisement for entertainment or activities is generated. The advertisement generation unit also selects an advertisement that best suits the user's emotions after viewing the advertisement based on the emotion estimation data. For example, if the user is relaxed, an advertisement for relaxation products or services is generated. In this way, the effectiveness of the advertisement can be improved by analyzing the user's emotions after viewing the advertisement and generating an advertisement that elicits a positive emotional response.

[0100] The advertisement generation system can further estimate the user's emotions, and based on the estimated user emotions, analyze the user's emotions after viewing the advertisement and identify the timing to elicit a positive emotional response. For example, the emotion estimation function is used to analyze the user's emotions after viewing the advertisement and identify the timing to elicit a positive emotional response. For example, the advertisement is delivered during a time period when the user is relaxed. The advertisement generation unit also analyzes the user's emotional state after viewing the advertisement in real time and immediately identifies the timing to elicit a positive emotional response. For example, the advertisement is delivered during a time period when the user is excited. The advertisement generation unit also selects the optimal timing for the user's emotions after viewing the advertisement based on the emotion estimation data. For example, the advertisement is delivered during a time period when the user is not feeling stressed. In this way, the effectiveness of the advertisement can be improved by analyzing the user's emotions after viewing the advertisement and identifying the timing to elicit a positive emotional response.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The personal information collection department collects personal information, such as the user's name, age, gender, contact information, information about interests, purchase history, and information based on social media activity. Step 2: The location information collection unit collects location information, such as GPS data, Wi-Fi location information, and beacon data. Step 3: The advertisement generation unit generates advertisements based on the personal information and location information collected by the personal information collection unit and location information collection unit. For example, it generates personalized advertisements using a generation AI and customizes advertisements based on the user's interests and current location. Step 4: The advertisement display unit displays the advertisement generated by the advertisement generation unit on digital signage. For example, the advertisement is displayed on digital signage installed around town or in a specific area, and the advertisement is updated in real time.

[0103] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0104] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0105] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0108] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0109] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0110] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0111] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0112] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0113] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0114] 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.

[0115] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0116] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0117] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0118] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0119] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0120] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0123] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0124] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0125] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0126] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0127] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0128] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0129] 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.

[0130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0132] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0133] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0134] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0135] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 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.

[0138] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0139] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0140] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0141] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0142] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0143] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0144] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0145] 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.

[0146] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0147] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0148] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0149] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0150] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0151] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0152] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0153] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0154] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0155] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0156] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0157] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0158] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0159] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0160] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0161] 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.

[0162] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0163] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0164] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0165] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0166] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0167] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0168] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0169] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a personal information collection department that collects personal information; a location information collection unit that collects location information; an advertisement generation unit that generates an advertisement based on the personal information and the location information collected by the personal information collection unit and the location information collection unit; an advertisement display unit that displays the advertisement generated by the advertisement generation unit on a digital signage. A system characterized by:

2. The advertisement generation unit Combining the user's past movement history and purchase history to predict future behavior and generate the advertisement based on that prediction 2. The system of claim 1.

3. The advertisement generation unit Analyze users' social media activity and reflect changes in interests in real time 2. The system of claim 1.

4. The advertisement generation unit Analyzing the user's current emotional state and generating the advertisement that matches that emotion 2. The system of claim 1.

5. The advertisement generation unit Collecting user health data and generating the advertisement according to the user's health condition 2. The system of claim 1.

6. The advertisement generation unit Collecting data from the user's home devices and generating the advertisement according to the home environment 2. The system of claim 1.

7. The advertisement generation unit Analyzing the emotions of users when they are in a specific location and generating the advertisement appropriate for that location 2. The system of claim 1.

8. The advertisement generation unit Combining the user's purchase history with the location information to generate the advertisement including special offers for specific stores or areas 2. The system of claim 1.

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